Abstract The ABM methodology is a favorable approach to model and analyze complex social phenomena that may involve non-linear feedback loops. It has been applied successfully to model a number of social phenomena involving different social processes and organizational structures. Availability of cheap computing power and rich software resources has made ABM a widely used and hence more popular methodology. A modeler using ABM however have be careful about choosing the right amount of detail (less and more both can be problematic) and validating (internal and external) the model. Interpreting and analyzing results is also an involved task. In this paper, we have demonstrated how ABM can be applied to model and analyze the voting preference formation and resultant voting decisions of individuals in a population. The model assumes a two party system. We designed three versions of the simulation and observed the results for a large number of runs with different parameter variations. The results obtained present interesting picture and resultant inferences.
The social network analysis (SNA), branch of complex systems can be used in the construction of multiagent
systems. This paper proposes a study of how social network analysis can assist in modeling multiagent
systems, while addressing similarities and differences between the two theories. We built a prototype
of multi-agent systems for resolution of tasks through the formation of teams of agents that are formed on
the basis of the social network established between agents. Agents make use of performance indicators to
assess when should change their social network to maximize the participation in teams.
Current trends of opinion mining and sentiment analysis in social networkseSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
The document discusses various internet services including search engines, social networks, and email. It provides details on how each service works, their history and evolution. Search engines aim to provide relevant results from a simple interface. Social networks allow studying relationships between individuals and groups. Email operates by storing and forwarding digital messages between users even when they are not online simultaneously, becoming a crucial tool in creating the internet. Standards for encoding email messages were proposed as early as 1973.
Hybrid sentiment and network analysis of social opinion polarization icoictAndry Alamsyah
The rapid growth of social media and user generated contents (UGC) has provided a rich source of potentially relevant data. The problems arise on how to summarize those data to understand and transforming it into information. Twitter as one of the most popular social networking and micro-blogging service can be analyzed in terms of content produced with sentiment analysis. On the other hand, some types of networks can also be constructed to analyze the social network structure and network properties. This research intended to combine those content and structural approaches into hybrid approach for identifies social opinion polarization, this is in the form of conversation network. Sentiment analysis used to determine public sentiment, and social network analysis used to analyze the structure of the network, detecting communities and influential actors in the network. Using this hybrid approach, we have comprehensive understanding about social opinion polarization. As case study, we present real social opinion polarization about reclamation issue in Indonesia.
Towards Validating Social Network SimulationsBruce Edmonds
A paper presented at ESSA 2013, Warsaw. Abstract: We consider the problem of finding suitable measures to validate simulated networks as outcome of (agent-based) social simulations. A number of techniques from computer science and social sciences are reviewed in this paper, which tries to compare and ‘fit’ various simulated networks to the avail-able data by using network measures. We look at several social network analy-sis measures but then turn our focus to techniques that not only consider the po-sition of the nodes but also their characteristics and their tendency to cluster with other nodes in the network – subgroup identification. We discuss how stat-ic and dynamic nature of networks may be compared. We conclude by urging a more comprehensive, transparent and rigorous approach to comparing simula-tion-generated networks against the available data.
This document summarizes research on social contagion using social network data. It describes analyzing the Framingham Heart Study network data (FHS-Net) of over 12,000 individuals connected through family, friendship, coworkers and neighbors over 30+ years. The researchers have also analyzed other datasets like the National Longitudinal Study of Adolescent Health. Their research has found evidence that behaviors, states and traits like obesity, smoking, happiness and depression show clustering within social networks, suggesting the spread of influence through network ties. The researchers acknowledge limitations of current methods and hope to help develop new statistical approaches for analyzing network data.
MULTI-AGENT PARADIGM FOR LEADERSHIP SELECTION: A REVIEWEditor IJMTER
A Multi-agent System (MAS) is comprised of multiple interacting intelligent agents. Agents
in the MAS could all be of same type (homogeneous) or different (heterogeneous). MAS are used to
solve problems which are either difficult for an individual agent to solve or when the problem is
inherently comprised of multiple actors interacting together. However, the nature of MAS design
coordination among agents in MAS is always a core issue. Coordination and cooperation allows the
agents to manage their inter dependencies and the type and nature of interactions. Coordination and
cooperation differ in degree of inter-agent knowledge and beliefs. Agent coordination is usually
achieved in the backdrop of a communication system between agents. This paper is a based on the
review of various work on selection of multi-agent for various task domain.
The document discusses how social networks and individual attitudes influence each other through two related processes: social contagion and homophily. Social contagion refers to the diffusion of attributes through a social network based on its structure, while homophily refers to the formation of social networks based on shared attributes among individuals. The document outlines Friedkin's model of social influence, which models how individuals' opinions are shaped both by their own characteristics and by interpersonal influences within their social network over multiple time periods.
The social network analysis (SNA), branch of complex systems can be used in the construction of multiagent
systems. This paper proposes a study of how social network analysis can assist in modeling multiagent
systems, while addressing similarities and differences between the two theories. We built a prototype
of multi-agent systems for resolution of tasks through the formation of teams of agents that are formed on
the basis of the social network established between agents. Agents make use of performance indicators to
assess when should change their social network to maximize the participation in teams.
Current trends of opinion mining and sentiment analysis in social networkseSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
The document discusses various internet services including search engines, social networks, and email. It provides details on how each service works, their history and evolution. Search engines aim to provide relevant results from a simple interface. Social networks allow studying relationships between individuals and groups. Email operates by storing and forwarding digital messages between users even when they are not online simultaneously, becoming a crucial tool in creating the internet. Standards for encoding email messages were proposed as early as 1973.
Hybrid sentiment and network analysis of social opinion polarization icoictAndry Alamsyah
The rapid growth of social media and user generated contents (UGC) has provided a rich source of potentially relevant data. The problems arise on how to summarize those data to understand and transforming it into information. Twitter as one of the most popular social networking and micro-blogging service can be analyzed in terms of content produced with sentiment analysis. On the other hand, some types of networks can also be constructed to analyze the social network structure and network properties. This research intended to combine those content and structural approaches into hybrid approach for identifies social opinion polarization, this is in the form of conversation network. Sentiment analysis used to determine public sentiment, and social network analysis used to analyze the structure of the network, detecting communities and influential actors in the network. Using this hybrid approach, we have comprehensive understanding about social opinion polarization. As case study, we present real social opinion polarization about reclamation issue in Indonesia.
Towards Validating Social Network SimulationsBruce Edmonds
A paper presented at ESSA 2013, Warsaw. Abstract: We consider the problem of finding suitable measures to validate simulated networks as outcome of (agent-based) social simulations. A number of techniques from computer science and social sciences are reviewed in this paper, which tries to compare and ‘fit’ various simulated networks to the avail-able data by using network measures. We look at several social network analy-sis measures but then turn our focus to techniques that not only consider the po-sition of the nodes but also their characteristics and their tendency to cluster with other nodes in the network – subgroup identification. We discuss how stat-ic and dynamic nature of networks may be compared. We conclude by urging a more comprehensive, transparent and rigorous approach to comparing simula-tion-generated networks against the available data.
This document summarizes research on social contagion using social network data. It describes analyzing the Framingham Heart Study network data (FHS-Net) of over 12,000 individuals connected through family, friendship, coworkers and neighbors over 30+ years. The researchers have also analyzed other datasets like the National Longitudinal Study of Adolescent Health. Their research has found evidence that behaviors, states and traits like obesity, smoking, happiness and depression show clustering within social networks, suggesting the spread of influence through network ties. The researchers acknowledge limitations of current methods and hope to help develop new statistical approaches for analyzing network data.
MULTI-AGENT PARADIGM FOR LEADERSHIP SELECTION: A REVIEWEditor IJMTER
A Multi-agent System (MAS) is comprised of multiple interacting intelligent agents. Agents
in the MAS could all be of same type (homogeneous) or different (heterogeneous). MAS are used to
solve problems which are either difficult for an individual agent to solve or when the problem is
inherently comprised of multiple actors interacting together. However, the nature of MAS design
coordination among agents in MAS is always a core issue. Coordination and cooperation allows the
agents to manage their inter dependencies and the type and nature of interactions. Coordination and
cooperation differ in degree of inter-agent knowledge and beliefs. Agent coordination is usually
achieved in the backdrop of a communication system between agents. This paper is a based on the
review of various work on selection of multi-agent for various task domain.
The document discusses how social networks and individual attitudes influence each other through two related processes: social contagion and homophily. Social contagion refers to the diffusion of attributes through a social network based on its structure, while homophily refers to the formation of social networks based on shared attributes among individuals. The document outlines Friedkin's model of social influence, which models how individuals' opinions are shaped both by their own characteristics and by interpersonal influences within their social network over multiple time periods.
Finding Pattern in Dynamic Network AnalysisAndry Alamsyah
1) The document analyzes social network properties like nodes, edges, average degree, diameter and average path length for different companies on Twitter over time.
2) It finds that network properties generally indicate more user interactions and information sharing on weekdays compared to weekends.
3) However, the diameter and average path length are often lowest on weekends, suggesting information spreads more quickly at those times due to the network structure.
The Mathematics of Social Network Analysis: Metrics for Academic Social NetworksEditor IJCATR
Social network analysis plays an important role in analyzing social relations and patterns of interaction among actors in a
social network. Such networks can be casual, like those on social media sites, or formal, like academic social networks. Each of these
networks is characterised by underlying data which defines various features of the network. Keeping in view the size and diversity of
these networks it may not be possible to dissect entire network with conventional means. Social network visualization can be used to
graphically represent these networks in a concise and easy to understand manner. Social network visualization tools rely heavily on
quantitative features to numerically define various attributes of the network. These features also referred to as social network metrics
used everyday mathematics as their foundations. In this paper we provide an overview of various social network analysis metrics that
are commonly used to analyse social networks. Explanation of these metrics and their relevance for academic social networks is also
outlined
This document provides an overview of different measures for analyzing social networks, including centrality measures, connectivity and cohesion measures, and roles. It discusses centrality measures like degree, closeness, betweenness, and eigenvector centrality for individual nodes. It also covers whole network measures like degree distribution, density, and centralization. The document describes local connectivity and cohesion measures including reciprocity, triad census, transitivity, and clustering coefficients. It discusses how these measures can be applied and interpreted for one-mode projections of two-mode networks.
This document discusses social network analysis and its implications for understanding power networks. Social network analysis maps the relationships between individuals in a network and can identify central actors as well as measures of power like degree centrality, closeness centrality, and betweenness centrality. The document recommends using social network analysis to understand power structures in organizations and teams in order to identify powerful individuals and propose influence tactics.
DYNAMIC LARGE SCALE DATA ON TWITTER USING SENTIMENT ANALYSIS AND TOPIC MODELINGAndry Alamsyah
1. The document presents a case study analyzing tweets about Uber using sentiment analysis and topic modeling to understand public opinion from large-scale social media data.
2. Sentiment analysis classified tweets as positive, negative, or neutral, while topic modeling identified dominant topics of discussion, like promotions or driver complaints.
3. The analyses found that positive tweets often discussed promotions while negative tweets addressed issues like sexual harassment allegations or unsatisfactory drivers.
I. The document discusses ego networks and how they can be used to study personal networks and relationships. Ego networks combine traditional survey data with network data by collecting information about respondents (egos) and their social ties (alters).
II. Ego network data can be used to examine the effects of network structure and alter characteristics on outcomes of interest. It can also provide insights into diffusion processes within personal networks.
III. While ego network data is useful for studying local network phenomena, global network data is needed to analyze higher-level structural effects, mechanisms of tie formation and diffusion across an entire network. Statistical techniques like randomization and the Quadratic Assignment Procedure are used to analyze ego and global network data
Scott Gomer presented on social network analysis (SNA). He reviewed literature on SNA and its use as a tool to analyze social structures and influence. He discussed SNA's capabilities in identifying key relationships and influencers through visual sociograms. However, SNA also has limitations such as complexity with large networks. Gomer collected binary data on relationships within a network and analyzed it using sociograms to illustrate examples of social link platforms. He concluded that SNA is a qualitative tool that can provide useful insights for marketing research by studying relationships.
Spatial statistics presentation Texas A&M Census RDCCorey Sparks
The purpose of this workshop is twofold. A primary goal is to provide researchers with a basic overview of spatial analysis. A secondary goal is to give attention to issues in GIS and spatial analysis that may be relevant to researchers planning to work with location data and unique geographies in confidential data sets in the Texas Census Research Data Center.
The workshop will consist of three sessions. Each session will be led by Dr. Corey Sparks, Assistant Professor at UTSA's College of Public Policy. Dr. Spark's research focuses on statistical demography, Geographic Information Systems and the application of modern statistical methods to problems in demography and health. His teaching interests focus on use and application of advanced statistical techniques including hazards analysis, multivariate methods and spatial statistics in human population analysis.
a modified weight balanced algorithm for influential users community detectio...INFOGAIN PUBLICATION
This document summarizes a research paper that proposes a modified algorithm for detecting influential user communities in online social networks. The paper first discusses existing community detection techniques and their limitations in identifying overlapping communities and influential kernel members. It then presents a new algorithm that uses Longest Chain Subsequence metrics to identify communities and their connections in a way that considers both highly connected and smaller communities. The algorithm is tested on Facebook network datasets and shown to outperform existing techniques in precision, recall, and F1-score for community detection.
Preso on social network analysis for rtp analytics unconferenceBruce Conner
Selected highlights of Coursera Social Networking course, taught by Prof. Lada Adamic of the Univ. of Michigan. Presented at the annual Annual RTP Analytics Unconference, May 4, 2013
Stochastic actor-oriented models (SAOMs) allow for the modeling of interdependent network and behavioral change over time. SAOMs conceptualize change as occurring through a sequence of micro-steps, with actors making decisions to change their ties or behaviors based on maximizing an objective function. The objective function specifies how different network and behavioral effects influence these decisions. SAOMs can be used to estimate the effects of network structure on behaviors or behaviors on network structure while accounting for endogenous network and behavioral processes.
This document discusses how social networks and relationships change over time. It covers two main ways time is incorporated: 1) how things like ideas diffuse through a network, and 2) how the network structure itself changes as relationships are formed or break. It also discusses different forces that can impact network dynamics, such as reciprocity, transitivity, balance, and structural holes. Simulation models are described that examine how simple rules about seeking transitivity or avoiding conflict can lead to the formation of cliques or more fluid network structures over time.
Social network analysis & Big Data - Telecommunications and moreWael Elrifai
Social Network Analysis: Practical Uses and Implementation is a presentation that discusses social network analysis and its uses. It covers key topics such as defining social networks and social network analysis, why social network analysis is important, identifying influencers in social networks, roles in social networks, graph theory concepts used in social network analysis, calculating metrics from social networks, and recommended approaches to social network analysis. The presentation provides an overview of social network analysis concepts and their practical applications.
People are generally inaccurate at recalling their own social networks and communications. Across seven experiments, participants could only accurately recall about 50% of their actual communications on average. Both over-reporting and under-reporting were issues, with people who communicate less tending to over-report and people who communicate more tending to under-report. While the inaccuracies cannot be entirely explained by factors like timing or reporting biases, they provide insight into cognitive processes and how perceptions of social networks are formed.
Brief tutorial on Influence and Homophily in social networks. Key concepts. How to distinguish influence from correlation. Information diffusion processes. Influence Maximization Problem
and viral marketing.
This document provides an overview of ego network analysis. It defines ego networks as consisting of a focal individual (ego) and the people they are connected to (alters). Various measures of ego network composition, structure, and properties can be analyzed, such as size, density, and homophily. These measures provide insight into an individual's social support and influence, and can be used to study health-related questions by examining the characteristics and behaviors present in one's social network. Ego network data is relatively easy to collect and can offer information about both individuals and inferred properties of broader social networks.
This document discusses social network analysis (SNA), a tool used to analyze social relationships and networks. SNA elicits, analyzes, and visualizes how actors interact and resources move through a network. It represents actors as nodes and their relationships as ties. The document provides examples of SNA's application in education, health, and agriculture. It outlines the process of conducting SNA through workshops or surveys to collect node attribute and tie/link data, which is then analyzed using software to visualize the network. The document suggests opportunities to further develop SNA, such as presenting networks back to communities and measuring social capital.
This document summarizes Michael Davern's proposed research agenda for applying social network analysis to economic sociology. It begins by outlining four key components of social networks: 1) structural, 2) resource, 3) normative, and 4) dynamic. It then reviews existing literature in economic sociology that utilizes social networks, such as studies of job searching and interlocking directorships. Finally, it proposes new areas for social networks to provide insights into socioeconomic behavior, such as combining the structural, resource, and normative dimensions over time. The overall aim is to demonstrate how social network analysis can create a more complete social science by integrating sociological and economic theories.
This document provides an overview of various measures for describing whole networks and individual nodes within networks. It discusses centrality measures like degree, closeness, betweenness, and power centrality. It also covers connectivity and cohesion measures like reciprocity, triad census, transitivity, clustering coefficient, and structural cohesion. The document uses examples from social networks to illustrate different measures and their implications for diffusion and information flow.
Este documento presenta preguntas sobre un juego desarrollado con Alice 2.2 que explora la aplicación de alimentos transgénicos en la biotecnología. Pregunta sobre los principales aprendizajes sobre los alimentos transgénicos del juego y las dificultades en su desarrollo y cómo se resolvieron. También pregunta cómo la revolución invisible de la biotecnología influye en nuestra calidad de vida.
The document provides guidance on effective networking for employment. It defines networking as relationship building and information gathering. Networking involves establishing trust and mutual benefit. The value of networking is more than just connecting with people in your field. Networking basics include showing gratitude, respect, etiquette, expectations, and tact. Networking can be done with colleagues, alumni, professional associations, and more. The goal is to find opportunities and stay informed.
Finding Pattern in Dynamic Network AnalysisAndry Alamsyah
1) The document analyzes social network properties like nodes, edges, average degree, diameter and average path length for different companies on Twitter over time.
2) It finds that network properties generally indicate more user interactions and information sharing on weekdays compared to weekends.
3) However, the diameter and average path length are often lowest on weekends, suggesting information spreads more quickly at those times due to the network structure.
The Mathematics of Social Network Analysis: Metrics for Academic Social NetworksEditor IJCATR
Social network analysis plays an important role in analyzing social relations and patterns of interaction among actors in a
social network. Such networks can be casual, like those on social media sites, or formal, like academic social networks. Each of these
networks is characterised by underlying data which defines various features of the network. Keeping in view the size and diversity of
these networks it may not be possible to dissect entire network with conventional means. Social network visualization can be used to
graphically represent these networks in a concise and easy to understand manner. Social network visualization tools rely heavily on
quantitative features to numerically define various attributes of the network. These features also referred to as social network metrics
used everyday mathematics as their foundations. In this paper we provide an overview of various social network analysis metrics that
are commonly used to analyse social networks. Explanation of these metrics and their relevance for academic social networks is also
outlined
This document provides an overview of different measures for analyzing social networks, including centrality measures, connectivity and cohesion measures, and roles. It discusses centrality measures like degree, closeness, betweenness, and eigenvector centrality for individual nodes. It also covers whole network measures like degree distribution, density, and centralization. The document describes local connectivity and cohesion measures including reciprocity, triad census, transitivity, and clustering coefficients. It discusses how these measures can be applied and interpreted for one-mode projections of two-mode networks.
This document discusses social network analysis and its implications for understanding power networks. Social network analysis maps the relationships between individuals in a network and can identify central actors as well as measures of power like degree centrality, closeness centrality, and betweenness centrality. The document recommends using social network analysis to understand power structures in organizations and teams in order to identify powerful individuals and propose influence tactics.
DYNAMIC LARGE SCALE DATA ON TWITTER USING SENTIMENT ANALYSIS AND TOPIC MODELINGAndry Alamsyah
1. The document presents a case study analyzing tweets about Uber using sentiment analysis and topic modeling to understand public opinion from large-scale social media data.
2. Sentiment analysis classified tweets as positive, negative, or neutral, while topic modeling identified dominant topics of discussion, like promotions or driver complaints.
3. The analyses found that positive tweets often discussed promotions while negative tweets addressed issues like sexual harassment allegations or unsatisfactory drivers.
I. The document discusses ego networks and how they can be used to study personal networks and relationships. Ego networks combine traditional survey data with network data by collecting information about respondents (egos) and their social ties (alters).
II. Ego network data can be used to examine the effects of network structure and alter characteristics on outcomes of interest. It can also provide insights into diffusion processes within personal networks.
III. While ego network data is useful for studying local network phenomena, global network data is needed to analyze higher-level structural effects, mechanisms of tie formation and diffusion across an entire network. Statistical techniques like randomization and the Quadratic Assignment Procedure are used to analyze ego and global network data
Scott Gomer presented on social network analysis (SNA). He reviewed literature on SNA and its use as a tool to analyze social structures and influence. He discussed SNA's capabilities in identifying key relationships and influencers through visual sociograms. However, SNA also has limitations such as complexity with large networks. Gomer collected binary data on relationships within a network and analyzed it using sociograms to illustrate examples of social link platforms. He concluded that SNA is a qualitative tool that can provide useful insights for marketing research by studying relationships.
Spatial statistics presentation Texas A&M Census RDCCorey Sparks
The purpose of this workshop is twofold. A primary goal is to provide researchers with a basic overview of spatial analysis. A secondary goal is to give attention to issues in GIS and spatial analysis that may be relevant to researchers planning to work with location data and unique geographies in confidential data sets in the Texas Census Research Data Center.
The workshop will consist of three sessions. Each session will be led by Dr. Corey Sparks, Assistant Professor at UTSA's College of Public Policy. Dr. Spark's research focuses on statistical demography, Geographic Information Systems and the application of modern statistical methods to problems in demography and health. His teaching interests focus on use and application of advanced statistical techniques including hazards analysis, multivariate methods and spatial statistics in human population analysis.
a modified weight balanced algorithm for influential users community detectio...INFOGAIN PUBLICATION
This document summarizes a research paper that proposes a modified algorithm for detecting influential user communities in online social networks. The paper first discusses existing community detection techniques and their limitations in identifying overlapping communities and influential kernel members. It then presents a new algorithm that uses Longest Chain Subsequence metrics to identify communities and their connections in a way that considers both highly connected and smaller communities. The algorithm is tested on Facebook network datasets and shown to outperform existing techniques in precision, recall, and F1-score for community detection.
Preso on social network analysis for rtp analytics unconferenceBruce Conner
Selected highlights of Coursera Social Networking course, taught by Prof. Lada Adamic of the Univ. of Michigan. Presented at the annual Annual RTP Analytics Unconference, May 4, 2013
Stochastic actor-oriented models (SAOMs) allow for the modeling of interdependent network and behavioral change over time. SAOMs conceptualize change as occurring through a sequence of micro-steps, with actors making decisions to change their ties or behaviors based on maximizing an objective function. The objective function specifies how different network and behavioral effects influence these decisions. SAOMs can be used to estimate the effects of network structure on behaviors or behaviors on network structure while accounting for endogenous network and behavioral processes.
This document discusses how social networks and relationships change over time. It covers two main ways time is incorporated: 1) how things like ideas diffuse through a network, and 2) how the network structure itself changes as relationships are formed or break. It also discusses different forces that can impact network dynamics, such as reciprocity, transitivity, balance, and structural holes. Simulation models are described that examine how simple rules about seeking transitivity or avoiding conflict can lead to the formation of cliques or more fluid network structures over time.
Social network analysis & Big Data - Telecommunications and moreWael Elrifai
Social Network Analysis: Practical Uses and Implementation is a presentation that discusses social network analysis and its uses. It covers key topics such as defining social networks and social network analysis, why social network analysis is important, identifying influencers in social networks, roles in social networks, graph theory concepts used in social network analysis, calculating metrics from social networks, and recommended approaches to social network analysis. The presentation provides an overview of social network analysis concepts and their practical applications.
People are generally inaccurate at recalling their own social networks and communications. Across seven experiments, participants could only accurately recall about 50% of their actual communications on average. Both over-reporting and under-reporting were issues, with people who communicate less tending to over-report and people who communicate more tending to under-report. While the inaccuracies cannot be entirely explained by factors like timing or reporting biases, they provide insight into cognitive processes and how perceptions of social networks are formed.
Brief tutorial on Influence and Homophily in social networks. Key concepts. How to distinguish influence from correlation. Information diffusion processes. Influence Maximization Problem
and viral marketing.
This document provides an overview of ego network analysis. It defines ego networks as consisting of a focal individual (ego) and the people they are connected to (alters). Various measures of ego network composition, structure, and properties can be analyzed, such as size, density, and homophily. These measures provide insight into an individual's social support and influence, and can be used to study health-related questions by examining the characteristics and behaviors present in one's social network. Ego network data is relatively easy to collect and can offer information about both individuals and inferred properties of broader social networks.
This document discusses social network analysis (SNA), a tool used to analyze social relationships and networks. SNA elicits, analyzes, and visualizes how actors interact and resources move through a network. It represents actors as nodes and their relationships as ties. The document provides examples of SNA's application in education, health, and agriculture. It outlines the process of conducting SNA through workshops or surveys to collect node attribute and tie/link data, which is then analyzed using software to visualize the network. The document suggests opportunities to further develop SNA, such as presenting networks back to communities and measuring social capital.
This document summarizes Michael Davern's proposed research agenda for applying social network analysis to economic sociology. It begins by outlining four key components of social networks: 1) structural, 2) resource, 3) normative, and 4) dynamic. It then reviews existing literature in economic sociology that utilizes social networks, such as studies of job searching and interlocking directorships. Finally, it proposes new areas for social networks to provide insights into socioeconomic behavior, such as combining the structural, resource, and normative dimensions over time. The overall aim is to demonstrate how social network analysis can create a more complete social science by integrating sociological and economic theories.
This document provides an overview of various measures for describing whole networks and individual nodes within networks. It discusses centrality measures like degree, closeness, betweenness, and power centrality. It also covers connectivity and cohesion measures like reciprocity, triad census, transitivity, clustering coefficient, and structural cohesion. The document uses examples from social networks to illustrate different measures and their implications for diffusion and information flow.
Este documento presenta preguntas sobre un juego desarrollado con Alice 2.2 que explora la aplicación de alimentos transgénicos en la biotecnología. Pregunta sobre los principales aprendizajes sobre los alimentos transgénicos del juego y las dificultades en su desarrollo y cómo se resolvieron. También pregunta cómo la revolución invisible de la biotecnología influye en nuestra calidad de vida.
The document provides guidance on effective networking for employment. It defines networking as relationship building and information gathering. Networking involves establishing trust and mutual benefit. The value of networking is more than just connecting with people in your field. Networking basics include showing gratitude, respect, etiquette, expectations, and tact. Networking can be done with colleagues, alumni, professional associations, and more. The goal is to find opportunities and stay informed.
This document discusses the influence of social media and online content sharing. It addresses why people share content online, the communities and memes that develop, and how sharing experiences online can shape one's professional profile and build awareness. The document outlines a group discussion activity where participants will discuss scenarios around building an online presence and the privacy implications of sharing content permanently online.
This document describes a music streaming app interface that includes menu options for favorites, playlists, search, and logout. The interface has tabs across the top for these main navigation categories.
After researching different media institutions, the author decided IPC media would be a good publisher for their magazine. IPC publishes over 60 brands popular with adults and has space in its market for a new magazine. IPC also publishes magazines on multiple platforms, suitable for the author's younger target audience. IPC currently has a large fan base that would grow with a new magazine for a different target audience. While IPC offers some magazines for teens, it could expand its offerings to fill a gap for specifically teenage-focused magazines in genres it does not currently cover like the author's proposed magazine.
A report issued by Pennsylvania's Independent Fiscal Office recapping the history of the state's impact fee collected on oil and gas development, and predicting what that fee may generate for state coffers in 2016. The report predicts a further slide in impact fee revenue from 2016 activity, due to the slowdown and continued weakness in natgas prices.
This document is a report on a teaching practicum conducted by 11 students from the Elementary School Teacher Education study program at the Muhammadiyah University of Cirebon. The practicum took place at SD Negeri 2 Lemahabang in Lemahabang village, Lemahabang sub-district, Cirebon regency. The report details the activities carried out and lessons learned during the practicum from February to April 2015.
This short document discusses a tree that stands out more in the springtime. It was used as part of a school project, and through the branches you can see the sun. The tree is perfect for the unspecified project being discussed.
Este documento describe las características y diferencias entre wikis y blogs. Explica que un wiki es un sitio web cuyas páginas pueden ser editadas por múltiples usuarios, permitiendo la creación colaborativa de contenido. Los blogs, por otro lado, son mantenidos principalmente por un solo autor. Aunque ambos son herramientas poderosas para la educación a distancia, un wiki fomenta más la colaboración mientras que un blog es más personal.
This document discusses semantical cognitive scheduling, which aims to improve process scheduling by considering the current state of the operating system. It proposes assigning a utility value to each process-state pair based on the semantical progress gained from running that process in that state. This allows the scheduler to maximize total utility by considering the current system state. Obtaining utility values can be done through machine learning, user feedback, or from software vendors. While the general problem of finding the optimal scheduling order is hard, complexity can be reduced by assuming the number of states is bounded. Dynamic programming and greedy approaches are proposed to find high-utility schedules in polynomial time by exploiting this bounded state space assumption.
Este documento describe varios insumos y herramientas para el mantenimiento de computadoras, incluyendo manillas antiestáticas, pinzas, desarmadores de precisión, probadores de fuente de poder, cables, baterías portátiles, linternas LED, sopladoras, brochas, latas de aire comprimido, limpiadores de pantalla, grasa para procesadores y alcohol isopropílico. Cada elemento se utiliza para una tarea específica como limpiar, conectar cables, retirar tornillos o revisar fallas.
The document discusses computer operating systems and file management. It defines an operating system as an interface between hardware and users that manages resources and coordinates activities. Operating systems handle hardware details, program execution, memory management, and more. Examples of operating systems include Windows, macOS, and real-time operating systems. File managers allow users to organize, view, and manage files and perform functions like copying, deleting, and moving files. Input devices like keyboards and mice provide data to computers while output devices like monitors and speakers communicate results.
The document discusses the importance of teachers' digital identities and provides strategies for managing digital footprints. It notes that teachers are held to a higher standard than other citizens and explores complex issues around social media use. The document outlines both appropriate and inappropriate social media activities for teachers and discusses how digital content can have unintended consequences due to issues like anonymity, persistence, replicability and searchability online. It emphasizes the need for teachers to make thoughtful decisions regarding sharing content and interacting with students online. Finally, the document provides tips for curating digital identities and online relationships with employers in mind.
Improving Knowledge Handling by building intellegent social systemsnazeeh
This document discusses improving knowledge handling by building intelligent systems using social agent modelling. It proposes capturing knowledge from social environments by developing new features in social network analysis systems and using this knowledge to model multi-agent systems. The approach involves extending social network analysis to cover more qualitative factors like emotions, relationships and trust to better represent knowledge and simulate agent behavior. Capturing these social aspects from real networks can provide criteria to analyze and design intelligent multi-agent systems.
Using Data Integration Modelsfor Understanding Complex Social SystemsBruce Edmonds
Describing the use of complex, descriptive simulations to integrate the maximum amount of evidence in a staged manner. With an example from the SCID project (http://www.scid-project.org).
Scalable recommendation with social contextual informationeSAT Journals
Abstract Recommender systems are used to achieve effective and useful results in a social networks. The social recommendation will provide a social network structure but it is challenging to fuse social contextual factors which are derived from user’s motivation of social behaviors into social recommendation. Here, we introduce two contextual factors in recommender systems which are used to adopt a useful results namely a) individual preference and b) interpersonal influence. Individual preference analyze the social interests of an item content with user’s interest and adopt only users recommended results. Interpersonal influence is analyzing user-user interaction and their specific social relations. Beyond this, we propose a novel probabilistic matrix factorization method to fuse them in a latent space. The scalable algorithm provides a useful results by analyzing the ranking probability of each user social contextual information and also incrementally process the contextual data in large datasets. Keywords: social recommendation, individual preference, interpersonal influence, matrix factorization.
Scalable recommendation with social contextual informationeSAT Journals
Abstract Recommender systems are used to achieve effective and useful results in a social networks. The social recommendation will provide a social network structure but it is challenging to fuse social contextual factors which are derived from user’s motivation of social behaviors into social recommendation. Here, we introduce two contextual factors in recommender systems which are used to adopt a useful results namely a) individual preference and b) interpersonal influence. Individual preference analyze the social interests of an item content with user’s interest and adopt only users recommended results. Interpersonal influence is analyzing user-user interaction and their specific social relations. Beyond this, we propose a novel probabilistic matrix factorization method to fuse them in a latent space. The scalable algorithm provides a useful results by analyzing the ranking probability of each user social contextual information and also incrementally process the contextual data in large datasets. Keywords: social recommendation, individual preference, interpersonal influence, matrix factorization
Running head DEPRESSION PREDICTION DRAFT1DEPRESSION PREDICTI.docxhealdkathaleen
This paper explores using machine learning and natural language processing techniques to analyze social media posts and other online behaviors to detect levels of depression in individuals. Key approaches discussed include using k-means clustering and neural networks on sources like reviews, posts, and articles. Link mining and weighted network modeling are also used to understand relationships between online content and detect patterns associated with depression. The goal is to help identify individuals who may be depressed so counselors can better assist them.
Patterns based information systems organization (@ InFuture 2015) Sergej Lugovic
Patterns-based Information Systems Organization
Sergej Lugović, Ivan Dunđer, Marko Horvat
Summary
The socio-technical systems research paradigm is about the complexity of real situations. It confronts us with the quest for variables that could provide us with insight into the behavior of such systems. Their behavior emerges according to internal system properties and adaptation of the system to external conditions.
In our view, behavioral patterns are one of those particular variables since machines can recognize them and their dynamics. Based on the synthesis of three different theoretical frameworks, this paper proposes a concept of patterns-based information system organization. The authors built the concept on the Deacon discussion of theory of information, Hofkirchner’s unified information theory and related system behavior, and Kelso’s explanation of pattern creation processes in self-organizing systems. All three researchers have included patterns in their theoretical proposal. According to this analysis of the existing theories and their synthesis, we conclude that in order to design machines that can automatically support new behavior, we have to analyze humans and machines as a complex whole with dynamic relationships and emerging patterns as a dependent variable of behavior. By developing this theoretical concept, we establish a departure point for future research and search for different variables that correlate with pattern formation.
Multimode network based efficient and scalable learning of collective behaviorIAEME Publication
This document discusses multimode network-based approaches for efficiently learning collective behavior in large social networks. It provides an overview of existing approaches for predicting collective behavior based on the behaviors of connected individuals. Specifically, it describes methods that extract social dimensions from networks to represent affiliations between actors and then apply supervised learning to determine which dimensions are informative for behavior prediction. However, existing approaches do not scale well to networks with millions of actors. The document proposes a new edge-centric clustering approach to extract sparse social dimensions, enabling the efficient handling of very large networks while maintaining predictive performance.
1) Values in Computational Models RevaluedComputational mode.docxmonicafrancis71118
1) Values in Computational Models Revalued
Computational models are mathematical representations that are designed to study the behaviour of complex systems. Systems under study are usually nonlinear and complex to the extent that conventional analytics cannot be used. Scholars have tried to establish the role played by trust and values in the use of such models in the analysis of public administration.
Public decision-making is itself a complex endeavour that involves the input of multiple stakeholders. Usually, there are a lot of conflicting interests that influence the final outcome of such decision-making processes (Klabunde & Willekens, 2016). In a computational model, a number of factors equally influence the outcome of the process. One of them is the number of actors involved –the presence of more actors normally implies increased mistrust. Another factor is the amount of trust that already exists among the decision makers. In cases where the group is homogenous, there is likely to be more trust and thus, less concern about the number of actors involved.
Given the importance of these two factors, the designer of any such model bears the largest burden in assuring the value of the model. He or she can choose to implement agency by humans or by technology depending on the number of actors and trust among them. Also, model designer determines the margins of error from each scenario while modelling (Gershman, Markman & Otto, 2014). Since in conventional decision-making processes different actors have different roles, the model designer may decide to accord different levels of authority to different actors. Nevertheless, they must ensure that such a decision does not affect the trust of the system. Overall, what values are sought from a computational model in a public decision-making context?
References
Gershman, S. J., Markman, A. B., & Otto, A. R. (2014). Retrospective revaluation in sequential decision making: A tale of two systems.
Journal of Experimental Psychology: General
,
143
(1), 182-194.
Klabunde, A., & Willekens, F. (2016). Decision-making in agent-based models of migration: state of the art and challenges.
European Journal of Population
,
32
(1), 73-97.
2) Active and Passive Crowdsourcing in Government
The authors of the article “Active and Passive Crowdsourcing in Government” discuss the application of the idea of crowdsourcing by public agencies. It leverages Web-based platforms to gather information from a large number of individuals for solving intricate problems (Loukis and Charalabidis 284). The scholars revealed that the concept of crowdsourcing was first adopted by organizations in the private sector, especially creative and design firms. Later on, state agencies began to determine how to leverage crowdsourcing to obtain “collective wisdom” from citizens aimed at informing the formulation and implementation of public policies.
Active and passive approaches to crowdsourcing are similar as they are both.
The evolution of the Web and its applications has undergone in the last few years a mutation towards
technologies that include the social dimension as a first class entity in which the users, their interactions
and the emerging social networks are the center of this evolution. The web is growing and evolving the
intelligibility of its resources and data, the connectivity of its parts and its autonomy as a whole system. The
social dimension of the current and future web is being at the roots of its dynamics and evolution. It is thus,
fundamental to propose new underlying infrastructure to the web and applications on the web, to make
more explicit this social dimension and facilitate its exploitation. The work presented is this paper
contributes to this initiative by proposing a multi-agent modeling based on the system coupling to its
environment through its social dimension. Applied to a collaborative tagging system, the exploitation of the
social dimension of tagging allows an intelligent and better sharing of resources and enhancing social
learning between users.
Assessment of the main features of the model of dissemination of information ...IJECEIAES
Social networks provide a fairly wide range of data that allows one way or another to evaluate the effect of the dissemination of information. This article presents the results of a study that describes methods for determining the key parameters of the model needed to analyze and predict the dissemination of information in social networks. An approach based on the analysis of statistical data on user behavior in social networks is proposed. The process of evaluating the main features of the model is described, including the mathematical methods used for data analysis and information dissemination modeling. The study aims to understand the processes of information dissemination in social networks and develop recommendations for the effective use of social networks as a communication and brand promotion tool, as well as to consider the analytical properties of the classical susceptible-infected-removed (SIR) model and evaluate its applicability to the problem of information dissemination. The results of the study can be used to create algorithms and techniques that will effectively manage the process of information dissemination in social networks.
This document provides an overview of a course on computational modelling for the social sciences. It introduces computational modelling as a methodology that uses models to study and solve complex problems in social phenomena. It discusses different types of models like conceptual, mathematical, physical and computational models. It explains key computational modelling approaches used in social sciences like social simulation, agent-based models, social network analysis and management information systems. The document outlines the course structure and provides contact and software details.
T OWARDS A S YSTEM D YNAMICS M ODELING M E- THOD B ASED ON DEMATELijcsit
This document proposes a new method for constructing system dynamics models that combines the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique with system dynamics modeling. DEMATEL is first used to systematically define and quantify causal relationships between variables in a system. The results from DEMATEL, including impact relation maps and a total influence matrix, are then used to derive the causal loop diagram and define variable weights in the stock-flow chart equations of the system dynamics model. This combined method aims to overcome limitations and subjectivity in traditional system dynamics modeling that relies solely on decision makers' mental models.
Sociometry and its application in social sciences researchPriyojoy Kar
This document provides an overview of sociometry, which is defined as measuring the social relationships and structure within groups. It discusses the history and development of sociometry by J.L. Moreno in the 1930s. The purposes, methods, and applications of sociometry are explained, including sociometric matrices, sociograms, and indices to analyze group dynamics. Steps in conducting sociometry with groups are outlined. Advantages include understanding interpersonal relationships and group structures, while limitations include relationships and responses may not be stable or fully revealed.
An improvised model for identifying influential nodes in multi parameter soci...csandit
Influence Maximization is one of the major tasks in the field of viral marketing and community
detection. Based on the observation that social networks in general are multi-parameter graphs
and viral marketing or Influence Maximization is based on few parameters, we propose to
convert the general social networks into “interest graphs”. We have proposed an improvised
model for identifying influential nodes in multi-parameter social networks using these “interest
graphs”. The experiments conducted on these interest graphs have shown better results than the
method proposed in [8].
A Literature Survey on Recommendation Systems for Scientific Articles.pdfAmber Ford
This document summarizes a literature survey on recommendation systems for scientific articles. It begins by outlining problems faced by researchers, including information overload from searching large amounts of non-structured data. It then reviews different types of recommender systems, including content-based, collaborative, knowledge-based, semantic-based, and hybrid approaches. The objective of the survey is to develop a framework for a semantic-based recommender system that integrates ontologies to help researchers more efficiently find relevant scientific articles.
The document summarizes a research paper that proposes a personalized recommendation approach combining social network factors like interpersonal interest similarity and interpersonal rating behavior similarity. It uses probabilistic matrix factorization to predict ratings by considering these social network factors. The approach is evaluated on two large real-world social rating datasets and shows improved performance over approaches that only use social network information.
Incremental Community Mining in Location-based Social NetworkIJAEMSJORNAL
A social network can be defined as a set of social entities connected by a set of social relations. These relations often change and differ in time. Thus, the fundamental structure of these networks is dynamic and increasingly developing. Investigating how the structure of these networks evolves over the observation time affords visions into their evolution structure, elements that initiate the changes, and finally foresee the future structure of these networks. One of the most relevant properties of networks is their community structure – set of vertices highly connected between each other and loosely connected with the rest of the network. Subsequently networks are dynamic, their underlying community structure changes over time as well, i.e they have social entities that appear and disappear which make their communities shrinking and growing over time. The goal of this paper is to study community detection in dynamic social network in the context of location-based social network. In this respect, we extend the static Louvain method to incrementally detect communities in a dynamic scenario following the direct method and considering both overlapping and non-overlapping setting. Finally, extensive experiments on real datasets and comparison with two previous methods demonstrate the effectiveness and potential of our suggested method.
Survey on personality predication methods using AIIJAEMSJORNAL
In this paper we present a deep Literature Survey on Personality. Personality is a psychological concept intended to explain the broad range of human behaviors in terms of a few, consistent and observable individual characteristics. In this regard, any technology that includes knowing, predicting and synthesizing human nature is likely to gain from technologies to Personality Computing, i.e. technologies that can deal with human character.This paper is a study of these technologies and seeks to provide not just a strong knowledge and understanding on the state-of – the art, and also a conceptual model underlying the three main issues discussed in the literature, Electronic Recognition of Character(Inference from behavioral knowledge of an individual or group true character),Automatic recognition of identities(Personality inference other people attribute to an applicant based on observable actions) and Automatic combination of identities (Artificial personality production by means of embodied agents).
Running head Multi-actor modelling system 1Multi-actor mod.docxtodd581
Running head: Multi-actor modelling system 1
Multi-actor modelling system3
Multi-actor modelling system
Yogesh Dagwale
University of the Cumberland’s
Ligtenberg, A., Wachowicz, M., Bregt, A. K., Beulens, A., & Kettenis, D. L. (2004). A design and application of a multi-agent system for simulation of multi-actor spatial planning. Journal of environmental management, 72(1-2), 43-55.
They talk about the potential and restrictions of the MAS to manufacture models that empower spatial organizers to incorporate the 'actor factor' in their examination. Their structure system contemplates actors who assume a functioning job in the spatial planning. They included actors who can watch and see a spatial domain. Using these perceptions and discernment they produce an inclination for a preferred spatial situation. Actors at that point present and discuss their inclinations amid their exchanges with different actors.
The inclinations of the actor fill in as inputs for an official choice making. Finally, ultimate conclusions are actualized in the spatial framework. They found that MAS can produce space utilization designs in light of a portrayal of a multi-actor planning process. It additionally can clear up the impacts of actors under the administration of various planning styles on the space utilization and prove how the relations between actors change amid a planning process and under different orders of coming up with decisions. Unlike the work by Parker, Manson, Janssen, Hoffman & Deadman,2003, cited below, this paper did not include the various challenges associated with the use of MAS.
Parker, D. C., Manson, S. M., Janssen, M. A., Hoffmann, M. J., & Deadman, P. (2003). Multi-agent systems for the simulation of land-use and land-cover change: a review. Annals of the association of American Geographers, 93(2), 314-337.
In this paper, they studied different models. These models, however, were not thorough enough and therefore they took into account the multi-actor system, dynamic spatial Simulation, which has two components, that is, a cellular model that speaks to biogeophysical and biological parts of a demonstrated framework and an actor-based model to speak to human conclusion making. Because of its nature and ability to model complex situations, they highlighted some of the areas that MAS can be applied where other models cannot be able to deliver. Such areas are modeling of emergent phenomena whereby MAS can model landscape plans, due to its flexibility, MAS can represent complex land use/ cover systems, and they can be used to model dynamic paths. They also outlined the various challenges to Multi-actor systems. Such challenges include an understanding of complexity, individual decision making, empirical parameterization and model validation, and communication.
Faber, N. R., & Jorna, R. J. (2011, June). The use of multi-actor systems for studying social sustainability: Theoretical backgrounds and pseudo-specifications. In Com.
Similar to Multi agent paradigm for cognitive parameter based feature similarity for social influence (20)
Mechanical properties of hybrid fiber reinforced concrete for pavementseSAT Journals
Abstract
The effect of addition of mono fibers and hybrid fibers on the mechanical properties of concrete mixture is studied in the present
investigation. Steel fibers of 1% and polypropylene fibers 0.036% were added individually to the concrete mixture as mono fibers and
then they were added together to form a hybrid fiber reinforced concrete. Mechanical properties such as compressive, split tensile and
flexural strength were determined. The results show that hybrid fibers improve the compressive strength marginally as compared to
mono fibers. Whereas, hybridization improves split tensile strength and flexural strength noticeably.
Keywords:-Hybridization, mono fibers, steel fiber, polypropylene fiber, Improvement in mechanical properties.
Material management in construction – a case studyeSAT Journals
Abstract
The objective of the present study is to understand about all the problems occurring in the company because of improper application
of material management. In construction project operation, often there is a project cost variance in terms of the material, equipments,
manpower, subcontractor, overhead cost, and general condition. Material is the main component in construction projects. Therefore,
if the material management is not properly managed it will create a project cost variance. Project cost can be controlled by taking
corrective actions towards the cost variance. Therefore a methodology is used to diagnose and evaluate the procurement process
involved in material management and launch a continuous improvement was developed and applied. A thorough study was carried
out along with study of cases, surveys and interviews to professionals involved in this area. As a result, a methodology for diagnosis
and improvement was proposed and tested in selected projects. The results obtained show that the main problem of procurement is
related to schedule delays and lack of specified quality for the project. To prevent this situation it is often necessary to dedicate
important resources like money, personnel, time, etc. To monitor and control the process. A great potential for improvement was
detected if state of the art technologies such as, electronic mail, electronic data interchange (EDI), and analysis were applied to the
procurement process. These helped to eliminate the root causes for many types of problems that were detected.
Managing drought short term strategies in semi arid regions a case studyeSAT Journals
Abstract
Drought management needs multidisciplinary action. Interdisciplinary efforts among the experts in various fields of the droughts
prone areas are helpful to achieve tangible and permanent solution for this recurring problem. The Gulbarga district having the total
area around 16, 240 sq.km, and accounts 8.45 per cent of the Karnataka state area. The district has been situated with latitude 17º 19'
60" North and longitude of 76 º 49' 60" east. The district is situated entirely on the Deccan plateau positioned at a height of 300 to
750 m above MSL. Sub-tropical, semi-arid type is one among the drought prone districts of Karnataka State. The drought
management is very important for a district like Gulbarga. In this paper various short term strategies are discussed to mitigate the
drought condition in the district.
Keywords: Drought, South-West monsoon, Semi-Arid, Rainfall, Strategies etc.
Life cycle cost analysis of overlay for an urban road in bangaloreeSAT Journals
Abstract
Pavements are subjected to severe condition of stresses and weathering effects from the day they are constructed and opened to traffic
mainly due to its fatigue behavior and environmental effects. Therefore, pavement rehabilitation is one of the most important
components of entire road systems. This paper highlights the design of concrete pavement with added mono fibers like polypropylene,
steel and hybrid fibres for a widened portion of existing concrete pavement and various overlay alternatives for an existing
bituminous pavement in an urban road in Bangalore. Along with this, Life cycle cost analyses at these sections are done by Net
Present Value (NPV) method to identify the most feasible option. The results show that though the initial cost of construction of
concrete overlay is high, over a period of time it prove to be better than the bituminous overlay considering the whole life cycle cost.
The economic analysis also indicates that, out of the three fibre options, hybrid reinforced concrete would be economical without
compromising the performance of the pavement.
Keywords: - Fatigue, Life cycle cost analysis, Net Present Value method, Overlay, Rehabilitation
Laboratory studies of dense bituminous mixes ii with reclaimed asphalt materialseSAT Journals
Abstract
The issue of growing demand on our nation’s roadways over that past couple of decades, decreasing budgetary funds, and the need to
provide a safe, efficient, and cost effective roadway system has led to a dramatic increase in the need to rehabilitate our existing
pavements and the issue of building sustainable road infrastructure in India. With these emergency of the mentioned needs and this
are today’s burning issue and has become the purpose of the study.
In the present study, the samples of existing bituminous layer materials were collected from NH-48(Devahalli to Hassan) site.The
mixtures were designed by Marshall Method as per Asphalt institute (MS-II) at 20% and 30% Reclaimed Asphalt Pavement (RAP).
RAP material was blended with virgin aggregate such that all specimens tested for the, Dense Bituminous Macadam-II (DBM-II)
gradation as per Ministry of Roads, Transport, and Highways (MoRT&H) and cost analysis were carried out to know the economics.
Laboratory results and analysis showed the use of recycled materials showed significant variability in Marshall Stability, and the
variability increased with the increase in RAP content. The saving can be realized from utilization of recycled materials as per the
methodology, the reduction in the total cost is 19%, 30%, comparing with the virgin mixes.
Keywords: Reclaimed Asphalt Pavement, Marshall Stability, MS-II, Dense Bituminous Macadam-II
Laboratory investigation of expansive soil stabilized with natural inorganic ...eSAT Journals
This document summarizes a study on stabilizing expansive black cotton soil with the natural inorganic stabilizer RBI-81. Laboratory tests were conducted to evaluate the effect of RBI-81 on the soil's engineering properties. The tests showed that with 2% RBI-81 and 28 days of curing, the unconfined compressive strength increased by around 250% and the CBR value improved by approximately 400% compared to the untreated soil. Overall, the study found that RBI-81 effectively improved the strength properties of the black cotton soil and its suitability as a soil stabilizer was supported.
Influence of reinforcement on the behavior of hollow concrete block masonry p...eSAT Journals
Abstract
Reinforced masonry was developed to exploit the strength potential of masonry and to solve its lack of tensile strength. Experimental
and analytical studies have been carried out to investigate the effect of reinforcement on the behavior of hollow concrete block
masonry prisms under compression and to predict ultimate failure compressive strength. In the numerical program, three dimensional
non-linear finite elements (FE) model based on the micro-modeling approach is developed for both unreinforced and reinforced
masonry prisms using ANSYS (14.5). The proposed FE model uses multi-linear stress-strain relationships to model the non-linear
behavior of hollow concrete block, mortar, and grout. Willam-Warnke’s five parameter failure theory has been adopted to model the
failure of masonry materials. The comparison of the numerical and experimental results indicates that the FE models can successfully
capture the highly nonlinear behavior of the physical specimens and accurately predict their strength and failure mechanisms.
Keywords: Structural masonry, Hollow concrete block prism, grout, Compression failure, Finite element method,
Numerical modeling.
Influence of compaction energy on soil stabilized with chemical stabilizereSAT Journals
This document summarizes a study on the influence of compaction energy on soil stabilized with a chemical stabilizer. Laboratory tests were conducted on locally available loamy soil treated with a patented polymer liquid stabilizer and compacted at four different energy levels. The study found that increasing the compaction effort increased the density of both untreated and treated soil, but the rate of increase was lower for stabilized soil. Treating the soil with the stabilizer improved its unconfined compressive strength and resilient modulus, and reduced accumulated plastic strain, with these properties further improved by higher compaction efforts. The stabilized soil exhibited strength and performance benefits compared to the untreated soil.
Geographical information system (gis) for water resources managementeSAT Journals
This document describes a hydrological framework developed in the form of a Hydrologic Information System (HIS) to meet the information needs of various government departments related to water management in a state. The HIS consists of a hydrological database coupled with tools for collecting and analyzing spatial and non-spatial water resources data. It also incorporates a hydrological model to indirectly assess water balance components over space and time. A web-based GIS portal was created to allow users to access and visualize the hydrological data, as well as outputs from the SWAT hydrological model. The framework is intended to facilitate integrated water resources planning and management across different administrative levels.
Forest type mapping of bidar forest division, karnataka using geoinformatics ...eSAT Journals
Abstract
The study demonstrate the potentiality of satellite remote sensing technique for the generation of baseline information on forest types
including tree plantation details in Bidar forest division, Karnataka covering an area of 5814.60Sq.Kms. The Total Area of Bidar
forest division is 5814Sq.Kms analysis of the satellite data in the study area reveals that about 84% of the total area is Covered by
crop land, 1.778% of the area is covered by dry deciduous forest, 1.38 % of mixed plantation, which is very threatening to the
environmental stability of the forest, future plantation site has been mapped. With the use of latest Geo-informatics technology proper
and exact condition of the trees can be observed and necessary precautions can be taken for future plantation works in an appropriate
manner
Keywords:-RS, GIS, GPS, Forest Type, Tree Plantation
Factors influencing compressive strength of geopolymer concreteeSAT Journals
Abstract
To study effects of several factors on the properties of fly ash based geopolymer concrete on the compressive strength and also the
cost comparison with the normal concrete. The test variables were molarities of sodium hydroxide(NaOH) 8M,14M and 16M, ratio of
NaOH to sodium silicate (Na2SiO3) 1, 1.5, 2 and 2.5, alkaline liquid to fly ash ratio 0.35 and 0.40 and replacement of water in
Na2SiO3 solution by 10%, 20% and 30% were used in the present study. The test results indicated that the highest compressive
strength 54 MPa was observed for 16M of NaOH, ratio of NaOH to Na2SiO3 2.5 and alkaline liquid to fly ash ratio of 0.35. Lowest
compressive strength of 27 MPa was observed for 8M of NaOH, ratio of NaOH to Na2SiO3 is 1 and alkaline liquid to fly ash ratio of
0.40. Alkaline liquid to fly ash ratio of 0.35, water replacement of 10% and 30% for 8 and 16 molarity of NaOH and has resulted in
compressive strength of 36 MPa and 20 MPa respectively. Superplasticiser dosage of 2 % by weight of fly ash has given higher
strength in all cases.
Keywords: compressive strength, alkaline liquid, fly ash
Experimental investigation on circular hollow steel columns in filled with li...eSAT Journals
Abstract
Composite Circular hollow Steel tubes with and without GFRP infill for three different grades of Light weight concrete are tested for
ultimate load capacity and axial shortening , under Cyclic loading. Steel tubes are compared for different lengths, cross sections and
thickness. Specimens were tested separately after adopting Taguchi’s L9 (Latin Squares) Orthogonal array in order to save the initial
experimental cost on number of specimens and experimental duration. Analysis was carried out using ANN (Artificial Neural
Network) technique with the assistance of Mini Tab- a statistical soft tool. Comparison for predicted, experimental & ANN output is
obtained from linear regression plots. From this research study, it can be concluded that *Cross sectional area of steel tube has most
significant effect on ultimate load carrying capacity, *as length of steel tube increased- load carrying capacity decreased & *ANN
modeling predicted acceptable results. Thus ANN tool can be utilized for predicting ultimate load carrying capacity for composite
columns.
Keywords: Light weight concrete, GFRP, Artificial Neural Network, Linear Regression, Back propagation, orthogonal
Array, Latin Squares
Experimental behavior of circular hsscfrc filled steel tubular columns under ...eSAT Journals
This document summarizes an experimental study that tested circular concrete-filled steel tube columns with varying parameters. 45 specimens were tested with different fiber percentages (0-2%), tube diameter-to-wall-thickness ratios (D/t from 15-25), and length-to-diameter (L/d) ratios (from 2.97-7.04). The results found that columns filled with fiber-reinforced concrete exhibited higher stiffness, equal ductility, and enhanced energy absorption compared to those filled with plain concrete. The load carrying capacity increased with fiber content up to 1.5% but not at 2.0%. The analytical predictions of failure load closely matched the experimental values.
Evaluation of punching shear in flat slabseSAT Journals
Abstract
Flat-slab construction has been widely used in construction today because of many advantages that it offers. The basic philosophy in
the design of flat slab is to consider only gravity forces; this method ignores the effect of punching shear due to unbalanced moments
at the slab column junction which is critical. An attempt has been made to generate generalized design sheets which accounts both
punching shear due to gravity loads and unbalanced moments for cases (a) interior column; (b) edge column (bending perpendicular
to shorter edge); (c) edge column (bending parallel to shorter edge); (d) corner column. These design sheets are prepared as per
codal provisions of IS 456-2000. These design sheets will be helpful in calculating the shear reinforcement to be provided at the
critical section which is ignored in many design offices. Apart from its usefulness in evaluating punching shear and the necessary
shear reinforcement, the design sheets developed will enable the designer to fix the depth of flat slab during the initial phase of the
design.
Keywords: Flat slabs, punching shear, unbalanced moment.
Evaluation of performance of intake tower dam for recent earthquake in indiaeSAT Journals
Abstract
Intake towers are typically tall, hollow, reinforced concrete structures and form entrance to reservoir outlet works. A parametric
study on dynamic behavior of circular cylindrical towers can be carried out to study the effect of depth of submergence, wall thickness
and slenderness ratio, and also effect on tower considering dynamic analysis for time history function of different soil condition and
by Goyal and Chopra accounting interaction effects of added hydrodynamic mass of surrounding and inside water in intake tower of
dam
Key words: Hydrodynamic mass, Depth of submergence, Reservoir, Time history analysis,
Evaluation of operational efficiency of urban road network using travel time ...eSAT Journals
This document evaluates the operational efficiency of an urban road network in Tiruchirappalli, India using travel time reliability measures. Traffic volume and travel times were collected using video data from 8-10 AM on various roads. Average travel times, 95th percentile travel times, and buffer time indexes were calculated to assess reliability. Non-motorized vehicles were found to most impact reliability on one road. A relationship between buffer time index and traffic volume was developed. Finally, a travel time model was created and validated based on length, speed, and volume.
Estimation of surface runoff in nallur amanikere watershed using scs cn methodeSAT Journals
Abstract
The development of watershed aims at productive utilization of all the available natural resources in the entire area extending from
ridge line to stream outlet. The per capita availability of land for cultivation has been decreasing over the years. Therefore, water and
the related land resources must be developed, utilized and managed in an integrated and comprehensive manner. Remote sensing and
GIS techniques are being increasingly used for planning, management and development of natural resources. The study area, Nallur
Amanikere watershed geographically lies between 110 38’ and 110 52’ N latitude and 760 30’ and 760 50’ E longitude with an area of
415.68 Sq. km. The thematic layers such as land use/land cover and soil maps were derived from remotely sensed data and overlayed
through ArcGIS software to assign the curve number on polygon wise. The daily rainfall data of six rain gauge stations in and around
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Multi agent paradigm for cognitive parameter based feature similarity for social influence
1. IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163
__________________________________________________________________________________________
Volume: 02 Issue: 04 | Apr-2013, Available @ http://www.ijret.org 687
MULTI-AGENT PARADIGM FOR COGNITIVE PARAMETER BASED
FEATURE SIMILARITY FOR SOCIAL INFLUENCE
Swati Basak1
, Bireshwar Dass Mazumdar2
, Chandra Bhan Patheriya3
1, 3
Dept. of Computer Engineering, SITM, Lucknow India, 2
SMS Varanasi India
swati.basak.bhu@gmail.com, bireshwardm@gmail.com, chandrabhan2006@gmail.com
Abstract
The ABM methodology is a favorable approach to model and analyze complex social phenomena that may involve non-linear
feedback loops. It has been applied successfully to model a number of social phenomena involving different social processes and
organizational structures. Availability of cheap computing power and rich software resources has made ABM a widely used and
hence more popular methodology. A modeler using ABM however have be careful about choosing the right amount of detail (less and
more both can be problematic) and validating (internal and external) the model. Interpreting and analyzing results is also an involved
task. In this paper, we have demonstrated how ABM can be applied to model and analyze the voting preference formation and
resultant voting decisions of individuals in a population. The model assumes a two party system. We designed three versions of the
simulation and observed the results for a large number of runs with different parameter variations. The results obtained present
interesting picture and resultant inferences.
--------------------------------------------------------------------***------------------------------------------------------------------------
1. INTRODUCTION
The development of social simulation over the past half
century can be grouped into three broad periods: macro
simulation, micro simulation and agent-based models.
Sociologists, particularly computational sociologists, first tried
macro simulations to model problems in supply-chain
management, inventory control in a warehouse, urban traffic,
and spread of epidemics, migration and demographic patterns.
Macro simulations consist of a set of differential equations
that take a holistic view of the system. However, taking the
complete system as the unit of analysis had inherent
limitations. Microsimulations focused on the use of
individuals as the unit of analysis but continued with macro-
level forecasting used in macrosimulations. Though
microsimulations modeled changes to each element of the
population but they did not permit individuals to directly
interact or to adapt. The main focus remained forecasting
macro effects of public policies that alter individual behaviors.
ABM, the third methodology, takes a pure bottom-up
approach and keeps the individual at the centre. It allows
modeling individual actors in the population and their
interactions with each other as well as with the environment.
This makes it a highly suitable technique for analysis of
emergent group behaviors resulting only from local
interactions of individuals. Besides, there are many other
advantages of this approach.
In Agent-based modeling (ABM) a system is modeled as a set
of autonomous agents, who can perceive the environment and
act on the basis of some behavioral rules. The agents represent
the actors in the system; environment represents the
surroundings including neighbouring agents; and the
behaviour rules model the interaction of the agent with other
agents as well as with the environment. ABM can be used to
model a number of phenomena in varied domains like Markets
& Economy, Organizations, World Wide Web and Social
Systems etc. Availability of fast and cheap computing power,
coupled with other advances in computational sciences has
paved the way for use of ABM as a preferred modeling and
simulation technique. Since last few years ABM has become
the frontrunner tool of the Sociologists and Psychologists who
try to model social cognitive parameter based behaviours,
particularly the behaviour of groups and societies. A large
number of researches are now being carried out using this
generative approach to model and analyze social phenomenon,
such as spread of rumors, diffusion of ideas, emergence of
cooperation, emergence of Conventions & social norms,
evolution and dynamics of spread of religions and cultures etc.
This paper presents our experimental work on using ABM for
understanding and analyzing cognitive parameter based voting
preferences of individuals. We have modeled the process and
factors shaping and affecting individual voting preferences for
a particular political party according to cognitive parameter
based. To keep the model simple and consequently analysis
more accurate, we have taken individual voting preferences as
„0‟ and „1‟ representing a two party political system. Every
individual‟s final voting decision is shaped and affected by a
number of factors, such as his own perception about parties,
his family views & beliefs, perception of his friends, and his
neighbourhood preferences. Our simulation models the role
and relative weights of these factors in shaping an individual‟s
voting preferences. We have also incorporated social influence
theory in our model which states that similar persons are more
2. IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163
__________________________________________________________________________________________
Volume: 02 Issue: 04 | Apr-2013, Available @ http://www.ijret.org 688
likely to interact, and as a result of frequent interactions they
are likely to become more similar.
2. ROLE OF AGENT BASED MODELING IN
SOCIAL INFLUENCE
Traditional modeling approaches to social influence systems
relied on equation-based models that operate with a macro
perspective. They operate on population attributes & their
distributions and lack the focus on individual‟s role. Equation-
based models, though useful for macro-scale behaviour
predictions, fail to model social influence systems (or
processes) that lack central coordination, systems that are very
complex in terms of their interdependencies and systems
which produce novel emergent behaviours in absence of a
clear understanding of the collective phenomenon. Axtell [1]
takes this argument a level further and suggests that there are
three distinct uses of Agent-based computational models of
social influence systems: (a) when numerical realizations can
be proposed and solved: agent models can be used as social
simulations; (b) when a mathematical model can be
formulated but can only be partially solved: agent based
models can be a useful tool of analysis; and (c) when
mathematical models are either apparently intractable or
provably insoluble: agent based modeling is perhaps the only
technique available for systematic analysis. Availability of fast
& cheap computing power along with rich easy-to-use
software environments also favours the use of ABM in Social
Sciences.
Although technically simple, ABM is conceptually deep.
Modeling a complex social process requires high conceptual
clarity and analytical ability. A key issue, therefore, is to
decide when to use ABM for modeling social influence
systems. An indicative list of situations when it is better to
think and model in terms of agents is: (a) when there is a
natural representation of actors as agents; (b) when the
interactions between the agents are complex, non-linear,
discontinuous, or discrete; (c) when agents exhibit complex
adaptive cognitive parameter based behaviours; (d) when the
population or topology of interactions is heterogeneous; and
(e) when agents have spatial component to their cognitive
parameter based behaviours & interactions. ABMs in social
sciences involve human agents, whose behaviours are often
complex, irrational and subjective. Therefore, one needs to
think carefully about the social phenomenon at hand before
going for ABM. Further, the model needs to be built at the
right level of description, with only the right amount of
details. Unnecessarily adding complexity to a model can make
the analysis difficult and the model useless.
ABM is currently being applied to model a variety of complex
social phenomenon where simple local interactions generate
emergent system-level behaviours. Some representative &
relevant work can be found in [1], [2], [3] & [4]. Macy &
Willer [3] group most of the work on Agent-based modeling
of collective behaviours in two categories: (a) models of
emergent structure which includes works on cultural
differentiation, homophilous clustering, idea diffusion,
convergent behaviours and norms; and (b) models of emergent
social order which include viability of trust, cooperation and
collective action in absence of global control. Goldstone &
Janssen [10] also identify three similar themes for Agent-
based computational models of collective behaviour namely:
(a) patterns and organizations which include settlement
patterns & segregation, human group behaviours and traffic
patterns; (b) social contagion which include spread of ideas,
fashions, cultures & religions; and (c) cooperation which
include evolution of cooperation, trust & reputations and
social norms & conventions.
3. SOCIAL INFLUENCE OF COGNITIVE
PARAMETERS
The Social influence assumes that individuals (or agents) often
imitate cognitive parameter based good behaviours and
cultures through their interactions with other individuals by
using coordination and cooperation (cognitive parameters). Its
dynamics depends on familiarity of the interacting individuals,
density of the neighbourhood, and popularity and spatial
proximity of the other individuals. The model of social
influence developed in two ways: (a) it explicitly takes into
account that the effect of one cultural feature depends on the
presence or absence of other cultural features and behaviours;
and (b) it takes into account that similar individuals are more
likely to influence each other than dissimilar individuals.
Interesting models of social influence have been proposed by
[4], [6], [7], [8], [9] etc. Axelrod [6] and [9], in his social
influence model of dissemination of culture [6], [9] focused on
factors of local influence (tendency for people who interact to
become more similar) and homophile (tendency to interact
more frequently with similar agents). The more agents
interact, the more similar they become; and the more similar
they become, the more likely they are to interact. Axelrod
expected convergence and homogeneity as the outcome but
simulation shown that despite the strong converging pressure,
stable regions of diversity persisted.
Axelrod [6] and [9] basic model included sites arrayed on a
grid. These sites are the basic actors of the model. Each site
can interact only with its immediate neighbours. Agents who
are similar to each other interact with each other and become
more similar. Axelrod‟s model captures culture as a group of
features with multiple trait values per features (cognitive
parameters). However, the emphasis is not on the content of a
specific culture but on the way in which culture is likely to
emerge and spread. The simulations with varying parameters
regarding grid size, number of features and number of traits
per feature resulted in polarization, despite the only
mechanism for change being convergence towards a
neighbour. We have used the basic idea of Axelrod‟s culture
model to represent friends of an individual [7]. An
3. IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163
__________________________________________________________________________________________
Volume: 02 Issue: 04 | Apr-2013, Available @ http://www.ijret.org 689
individual‟s friend is believed to have cognitive parameter
based behavioural feature set (cognitive parameter set) similar
to the individual. The feature set similarity represents their
like mindedness of the individuals on various issues and hence
possibility of having similar voting preferences (example of
model) or at least being affected by each other‟s preferences.
An individual while deciding about his vote (example model)
is thus likely to be affected by his interactions with friends.
Take an example of cognitive social influence model of
voting; an individual makes up his voting preference through a
complex process involving non-linear feedback loop of
interactions with a number of entities. Individuals interact with
frequently with their family members and relatively less
frequently with other persons belonging to their social and
religious groups. An individual‟s final voting value is no
doubt a function of these cognitive factors. However, what is
more important to understand is that what is the extent of this
effect and the by what underlying process an individual finally
makes up his voting preference. This model can be solved by
Greedy Approach and Case Base Reasoning (CBR) method,
some weighted values are assigned to the cognitive parameters
to decide the final voting preference of an individual; the CBR
method will be discussed in next section.
4. VOTING MODEL WITH FEATURE
SIMILARITY
In this Voting Model initially setup is design in such a manner
that all the individuals in grid or a particular area are assigning
with randomly votes and randomly assign feature set which
will decide final vote of individuals after dynamic interaction
among neighbour agents.
Model Setup
A population of agents is created on a wrap-around agent grid
of size 40 X 40. The key entities in the model are represented
by patches; each patch of the grid represents an agent. The
patches represent stationary landscape on the grid. In this
version agent hold a set of features. Each feature is a variable
that can adopt a binary value (1 or 0). Initially, agents adopt
randomly chosen a set of features. If feature size is n than
there will be 2n different type of feature set. Every agent has
one of this 2n feature set.
Model Parameters
In grid, we have placed agents at each coordinate. Every
individual has certain attributes that characterize it. Most
interestingly, it has a cognitive parameter based behavioural
feature set of size “n”, which can be a 1 to 10 bit string. Every
value in the string is a binary value (0 or 1) and represents a
particular feature. The feature set values of two agents is used
to decide whether they are sufficiently likeminded or not. Two
individuals having will be similar if their feature set string
contains a minimum number of similar feature values (greater
than a similarity threshold). An individual is more likely to be
influenced by those who are similar to him. In addition to the
feature set, every agent also has a voting preference value (1
or 0), initialized randomly. Before deciding his final voting
preference, an agent interacts with various agents in its
neighbourhood. According to social influence theory, it is
more likely to interact and be affected by the agents similar to
it. Interactions between similar agents make them more
similar. However, rather than changing the feature set values
of agents, we have changed their voting preference values so
that similar agents are more likely to have similar voting
preferences. In fact, the model picks up an agent and samples
its neighbourhood. Suppose n out of total m agents in the
neighbourhood are similar to the agent. Then the voting
preference of the agent changes to the majority preference of
the similar agents. In case of tie the agent retains its voting
preference. We obtained multiple runs of the model by
varying (i) the feature size, (ii) feature threshold size and (iii)
initial voting preference value distribution.
5. RESULTS
In these model multiples Runs are taken by varying feature
size, threshold size and initial voting preference value
distribution. The feature size “n” has been varied from 1 to 10
with feature similarity threshold being varied from 1 to n. Fig.
1 to Fig. 7 presents some initial and final snapshots of voting
model with feature similarity.
1(a) 1(b)
Fig. 1: A snapshot of the run of feature set based simulation.
The feature set size is 7 and similarity threshold is 1. The
initial values of green = 840 and blue = 841 (Fig. 1(a)),
transform to final values of green = 856 and blue = 825 and
stability time tick =10 (Fig. 1(b))
Table 1 shows few more of sampling runs by taking the above
data which describes the stability of model; time to stability
increases with decreasing the threshold size. It also shows if
threshold size nearer to feature size there will be less
polarization
4. IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163
__________________________________________________________________________________________
Volume: 02 Issue: 04 | Apr-2013, Available @ http://www.ijret.org 690
Table 1: Sample Runs of Feature Based Voting Model
CONCLUSIONS
The ABM methodology is a favorable approach to model and
analyze complex social phenomena that may involve non-
linear feedback loops. It has been applied successfully to
model a number of social phenomena involving different
social processes and organizational structures. Availability of
cheap computing power and rich software resources has made
ABM a widely used and hence more popular methodology. A
modeler using ABM however have be careful about choosing
the right amount of detail (less and more both can be
problematic) and validating (internal and external) the model.
Interpreting and analyzing results is also an involved task. In
this paper, we have demonstrated how ABM can be applied to
model and analyze the voting preference formation and
resultant voting decisions of individuals in a population. The
model assumes a two party system. We designed three
versions of the simulation and observed the results for a large
number of runs with different parameter variations. The results
obtained present interesting picture and resultant inferences.
The initial voting preference distribution in the population,
role of friends (likeminded individuals), affect of family
members and neighbours; all produce interesting results to
analyze. Social influence theory incorporated into voting
dynamics plays an important role. Individuals‟ voting
decisions are affected more by those who are similar to them.
However, if the similarity threshold is relatively lower, the
model results in local voting preference polarizations. When
the model is based only on majority, the initial distribution of
voting preferences becomes the key deciding factor. Both
these results taken together present similarity to the actual
voting patterns observed in closely knit societies and
segregations such as far off villages and tribal groups. The role
of implicit favorable waves introduced by mass media can also
be understood by the results of the second version of the
simulation. When the weights of factors playing role in
shaping an individual‟s voting preference are varied, the
results demonstrate that high weight to individual vote is able
to sustain variations in voting preferences. When the own-
weight is reduced to give more favour on the basis of
cognitive values to the family and neighbours, polarizing
tendency gains comes in and slight amount of local
polarization is seen in even in case of almost uniform initial
voting preference distribution. Voting behaviour and patterns
of relatively informed and well-educated persons conform to
this trend. The experimental simulations attempt to model an
interesting social cognitive phenomenon and present
interesting results that need to be further analyzed to draw
relevant inferences, analogies and explanations.
REFERENCES
[1]. J.M. Epstein, “Generative Social Sciences: Studies in
Agent-based Computational Modeling”, Princeton University
Press, (2007).
[2] J.M. Epstein & R. Axtell, “Growing Artificial Societies:
Socail science from bottom-up”, Cambridge, MA: MIT Press,
(1996).
[3]. M.W. Macy & R. Willer, “From factors to actors:
computational sociology and agent based modeling”, Annual
Review of Sociology, Vol. 28, pp. 143-166, (2002).
[4]. N. Gilbert & K. Troitzsch, “Simulation for the Social
Scientist”, Buckingham, U.K.: Open Univ. Press, (1999).
[5].R. Axelrod, “The Complexity of cooperation”, Princeton
N.J., Princeton University Press, (1997).
No. of
Runs
Fe
at
ur
e
Si
ze
Th
res
hol
d
Siz
e
No. of Green
Vote
No. of
Blue Vote
Tim
e to
Sta
ble
Initi
al
Final Initi
al
Fin
al
Run-1 7 1 840 856 841 825 10
Run-2 7 2 840 960 841 721 7
Run-3 7 3 840 860 841 821 7
Run-4 7 4 840 834 841 847 3
Run-5 7 5 840 838 841 843 2
Run-6 7 6 840 841 841 840 2
Run-7 7 7 840 840 841 841 1
Run-8 5 3 169 104 151
2
157
7
4
Run-9 5 3 505 417 117
6
126
4
3
Run-
10
5 3 673 610 100
8
107
1
4
Run-
11
3 2 169 144 151
2
153
7
3
Run-
12
3 2 505 458 117
6
122
3
2
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