The document provides an overview of social network analysis. It discusses:
1) A lecture on the history and basics of social network analysis, including what networks are, different types of networks (egonetworks, whole networks), relationships, and data collection methods.
2) A tutorial on organizing student groups and selecting topics.
3) The second part of the lecture covers data collection methods like name generators, position generators, and roster methods for collecting egonetwork and whole network data through surveys.
1. The document discusses relational sociology, which views social relations as the most important concept and analysis unit. It focuses on the works of key figures in relational sociology like Harrison White and John Levi Martin. 2. White developed concepts like identity, footing, switchings, and netdoms to analyze social phenomena through a network lens. Martin advocated field theory and heuristics to understand subjective social structures. 3. Relational sociology is compared to analytical sociology, with both sharing a focus on processes but differing in their units of analysis - relations versus actions.
This document provides an overview of social networks from a sociological perspective. It discusses social networks at the micro, meso, and macro levels of analysis and outlines several theoretical approaches and research areas within social network analysis, including structural holes, diffusion of innovations, organizational studies, and social media networks. Network science concepts like small-world networks, scale-free networks, and centrality metrics are also summarized.
Intro to social network analysis | What is Network Analysis? | History of (So...Gaditek
Social network analysis examines the connections between individuals, groups, organizations, or other social entities. It focuses on interactions rather than individual behavior. Network analysis can be applied across many disciplines to study how the structure of relationships influences functioning. Early research in fields like sociology, anthropology, and educational psychology helped develop concepts still used today, such as examining homophily and interaction patterns. Key concepts in network analysis include nodes, edges, degree, clustering coefficients, and graph diameter. "Small world" networks are highly clustered with short path lengths, characteristics seen in many real-world networks. Social capital research also examines how network connections impact groups, organizations, and individuals.
Mathematical Models of the Spread of Diseases, Opinions, Information, and Mis...Mason Porter
This is my general-audience talk at DiscCon III (2021 WorldCon).
My talk overlapped with the Hugo Award ceremony, but the video will be posted later on the DisCon website for attendees who want to see it.
This is my attempt at an introduction to data ethics for mathematicians. Mathematicians increasingly need to deal with these kinds of issues, but we don't have the tradition of ethics training from other disciplines.
I welcome comments on how to improve these slides. Did I miss any salient points? Do you want to offer a different perspective on any of these? Do you want to offer any counterpoints? (Please e-mail me directly with comments and suggestions.)
Eventually, I hope to develop these slides further into an article for a venue aimed at mathematical scientists, and of course I would love to have knowledgeable coauthors who can offer a different perspective from mine.
This document summarizes three types of field experiments related to social networks:
1) Peer effects experiments examine whether individual j influences the behaviors or outcomes of individual i. Examples test whether encouraging individual i to vote or buy a product also influences their friend j.
2) Network formation experiments study what factors affect whether individual i forms a network tie with individual j. Examples test how anonymity, search costs, and interactions affect network tie formation.
3) Designing networks experiments evaluate which network structures maximize outcomes at the network level. Examples design peer groups and seed farmers to test how network structure impacts behavior diffusion.
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.
1. The document discusses relational sociology, which views social relations as the most important concept and analysis unit. It focuses on the works of key figures in relational sociology like Harrison White and John Levi Martin. 2. White developed concepts like identity, footing, switchings, and netdoms to analyze social phenomena through a network lens. Martin advocated field theory and heuristics to understand subjective social structures. 3. Relational sociology is compared to analytical sociology, with both sharing a focus on processes but differing in their units of analysis - relations versus actions.
This document provides an overview of social networks from a sociological perspective. It discusses social networks at the micro, meso, and macro levels of analysis and outlines several theoretical approaches and research areas within social network analysis, including structural holes, diffusion of innovations, organizational studies, and social media networks. Network science concepts like small-world networks, scale-free networks, and centrality metrics are also summarized.
Intro to social network analysis | What is Network Analysis? | History of (So...Gaditek
Social network analysis examines the connections between individuals, groups, organizations, or other social entities. It focuses on interactions rather than individual behavior. Network analysis can be applied across many disciplines to study how the structure of relationships influences functioning. Early research in fields like sociology, anthropology, and educational psychology helped develop concepts still used today, such as examining homophily and interaction patterns. Key concepts in network analysis include nodes, edges, degree, clustering coefficients, and graph diameter. "Small world" networks are highly clustered with short path lengths, characteristics seen in many real-world networks. Social capital research also examines how network connections impact groups, organizations, and individuals.
Mathematical Models of the Spread of Diseases, Opinions, Information, and Mis...Mason Porter
This is my general-audience talk at DiscCon III (2021 WorldCon).
My talk overlapped with the Hugo Award ceremony, but the video will be posted later on the DisCon website for attendees who want to see it.
This is my attempt at an introduction to data ethics for mathematicians. Mathematicians increasingly need to deal with these kinds of issues, but we don't have the tradition of ethics training from other disciplines.
I welcome comments on how to improve these slides. Did I miss any salient points? Do you want to offer a different perspective on any of these? Do you want to offer any counterpoints? (Please e-mail me directly with comments and suggestions.)
Eventually, I hope to develop these slides further into an article for a venue aimed at mathematical scientists, and of course I would love to have knowledgeable coauthors who can offer a different perspective from mine.
This document summarizes three types of field experiments related to social networks:
1) Peer effects experiments examine whether individual j influences the behaviors or outcomes of individual i. Examples test whether encouraging individual i to vote or buy a product also influences their friend j.
2) Network formation experiments study what factors affect whether individual i forms a network tie with individual j. Examples test how anonymity, search costs, and interactions affect network tie formation.
3) Designing networks experiments evaluate which network structures maximize outcomes at the network level. Examples design peer groups and seed farmers to test how network structure impacts behavior diffusion.
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.
Networks & Health
This document provides an introduction and overview of social network analysis and its relevance to health research. It discusses key concepts such as what networks are, different types of network data including one-mode and two-mode data, and different levels of analysis including ego networks, partial networks, and complete networks. The document also discusses why networks matter for health through connectionist mechanisms like diffusion and positional mechanisms like social roles. Overall, the document serves as a high-level introduction to social network concepts and their application to health research.
Introduction to Social Network AnalysisPatti Anklam
This document provides an overview of network analysis and its applications. It discusses the origins and history of network study in fields like graph theory and sociology. Various network patterns and metrics are described, including density, distance, centrality, and structural measures. Case studies are presented on using network analysis to understand expertise management, trust, and performance issues in organizations. The document emphasizes that network analysis can provide insights through metrics and visualization to inform important business and organizational questions.
Power no longer resides exclusively (if at all) in states, institutions, or large corporations. It is located in the networks that structure society. Social network analysis seeks to understand networks and their participants and has two main focuses: the actors and the relationships between them in a specific social context.
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.
Subscriber Churn Prediction Model using Social Network Analysis In Telecommun...BAINIDA
Subscriber Churn Prediction Model using Social Network Analysis In Telecommunication Industry โดย เชษฐพงศ์ ปัญญาชนกุล อาจารย์ ดร. อานนท์ ศักดิ์วรวิชญ์
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Social Network Analysis & an Introduction to ToolsPatti Anklam
This document provides an introduction to social network analysis. It discusses how networks can be mapped and analyzed using tools to understand their structure and flow of information. Key aspects of network analysis are introduced, including nodes, ties, centrality metrics, and structural patterns. A variety of tools are presented, ranging from free social media applications to specialized software, that can be used to map and analyze networks. The value of network analysis is in identifying influential individuals, improving collaboration and knowledge sharing, and intervening to change network structures and behaviors.
An interactive presentation on social network theory and analysis. Content includes information on tie formation and social capital. Network relations are explained by using the example of The A Team. Granovetter's Strength of Weak Ties Theory (1973) is also covered and weak ties and strong ties are explained. Appropriate application of social network theory to individuals understanding how to best take advantage of social networking platforms to find jobs as well as companies taking advantage of social media platforms to find followers are introduced.
Small Worlds of Ambridge: Power, Networks & Actants Nicola Headlam
Seeking to explore the ways in which multi-dimensional power may be deployed within a spatially defined place needs an interrogation of place-based statecraft. The paper presents some of the forms of capital in play in Ambridge mapped using Social Network Analysis (SNA) It argues that the extant matriarchal structure of Aldridges/Archers can be challenged by Kinship structures emphasising the weak ties, or hinges between the major cliques/clans and that within the knowledge economy Ed's multiple contractual connections make him 'King of Ambridge'
The document discusses the "querelle" or debate between network science and the new social physics. It notes that the new social physics revisited ideas like small world theory and identified networks exhibiting "small worldliness," but were criticized for lacking sociological perspective. Watts argued small world networks can emerge from random ties between nodes, but others like Granovetter and Barabasi showed real networks have non-random structures. The document argues the small world thinkers overlook sociological factors like meaning, social relations, and inequality. It notes a problem for sociology of science as the physicists do not cite foundational work in social network analysis.
Social Network Analysis: What It Is, Why We Should Care, and What We Can Lear...Xiaohan Zeng
This document provides an overview of social network analysis, including what social networks are, what can be learned from analyzing social networks, and how social network analysis can be performed. Some key findings that can be uncovered include the six degrees of separation principle, the 80-20 rule of social popularity where a minority of nodes have most connections, how to identify influential nodes, and how to group similar nodes into communities. Various metrics and models are described for analyzing features like path lengths, degree distributions, ranking nodes, measuring community structure, and more. Examples of social network analysis are also provided.
This workshop will introduce some of the main principles and techniques of Social Network Analysis (SNA). We will use examples from organizational and social media-based networks to understand concepts such as network density, diameter, centrality measures, community detection algorithms, etc. The session will also introduce Gephi, a popular program for SNA. Gephi is a free and open-source tool that is available for both Mac and PC computers.
By the end of the session, you will develop a general understanding of what SNA is, what research questions it can help you answer, and how it can be applied to your own research. You will also learn how to use Gephi to visualize and examine networks using various layout and community detection algorithms.
Instructor’s Bio: Dr. Anatoliy Gruzd is a Canada Research Chair in Social Media Data Stewardship, Associate Professor at the Ted Rogers School of Management at Ryerson University, and Director of Research at the Social Media Lab. Anatoliy is also a Member of the Royal Society of Canada’s College of New Scholars, Artists and Scientists; a co-editor of a multidisciplinary journal on Big Data and Society; and a founding co-chair of the International Conference on Social Media and Society. His research initiatives explore how social media platforms are changing the ways in which people and organizations communicate, collaborate and disseminate information and how these changes impact the norms and structures of modern society.
This document provides 25 potential essay questions for a theory and methods course in sociology. The questions assess various sociological theories and perspectives, such as structuralism, functionalism, conflict theory, feminism, postmodernism, and evaluate debates around objectivity, value-freeness, and the scientific status of sociology. Additional questions address research methods like participant observation, surveys, interviews and use of quantitative vs qualitative data.
This document outlines the key concepts and lessons for Unit 1 of a sociology course. The unit will examine the foundations and origins of sociology, the three major theoretical perspectives in sociology, and how sociological research is conducted. Students will learn about the development of sociology as an academic discipline in response to social changes in Europe. They will also explore the functionalist, conflict, and interactionist perspectives and how sociologists use various methods like surveys, experiments, and observation to study social phenomena scientifically.
This document provides an overview of the first unit in a sociology course. It includes information about the first day of class procedures and an outline of topics to be covered in Unit 1. The unit will focus on examining social life, the development of sociology, modern sociological perspectives, and conducting sociological research. Students will learn about the origins of sociology, the three major theoretical perspectives (functionalism, conflict theory, and symbolic interactionism), and how sociological research follows the scientific method and ethical guidelines.
This document provides an overview of the first unit of a sociology course. It includes:
- An introduction to examining social life, including defining sociology and differentiating it from other social sciences.
- An outline of the development of sociology from the 17th-19th centuries in Europe in response to industrialization and other social changes. Key early theorists who contributed to the field are identified.
- An introduction to the three major theoretical perspectives in sociology - functionalism, conflict theory, and symbolic interactionism - and how they differ in their levels of analysis.
- An overview of how sociological research is conducted scientifically, using methods like surveys, observation, and experiments while following ethical standards
The document discusses several dominant approaches in the social sciences including:
1) Microlevel approaches like rational choice theory and symbolic interactionism that focus on individual behavior.
2) Macrolevel approaches like structural functionalism and institutionalism that examine larger social systems and structures.
3) Interdisciplinary approaches such as the human-environment system that integrate ideas across fields.
It then provides more details on specific theories under the microlevel and macrolevel categories.
This document discusses several dominant approaches and ideas in the social sciences. It outlines microlevel approaches like rational choice theory and symbolic interactionism, which focus on individual behavior and decision-making. It also discusses macrolevel approaches like structural functionalism and institutionalism, which examine larger social systems and structures. Structural functionalism views society as a complex system whose parts work together to promote stability. Institutionalism studies how formal and informal institutions influence social behavior by constraining and empowering individuals. The document provides overviews of the key concepts and premises of these different theoretical perspectives in social science.
Symbolic Interactionism, Structural-Functional Theory and Conflict Theory Vijayalakshmi Murugesan
This document provides an overview of three major sociological theories: symbolic interactionism, structural-functional theory, and conflict theory. Symbolic interactionism examines how individuals construct meanings through interactions and symbols. Structural-functional theory views society as a system of interrelated parts that work together to maintain stability. Conflict theory sees society as groups competing for limited resources and views social institutions as maintaining inequality between groups.
These slides are for my talk for the Somerville College Mathematics Reunion ("Somerville Maths Reunion", 6/24/17): http://www.some.ox.ac.uk/event/somerville-maths-reunion/
Talcott Parsons was an American sociologist who developed structural functionalism, which views society as a system of interconnected parts that work together to maintain stability and social order. Parsons was influenced by theorists like Durkheim, Weber, Spencer, and Comte. He developed theories of social action, the social system, AGIL functions, and pattern variables. Parsons viewed society as made up of interdependent institutions that help society adapt, attain goals, integrate, and maintain social order. He believed rapid social change could disrupt this equilibrium.
Networks & Health
This document provides an introduction and overview of social network analysis and its relevance to health research. It discusses key concepts such as what networks are, different types of network data including one-mode and two-mode data, and different levels of analysis including ego networks, partial networks, and complete networks. The document also discusses why networks matter for health through connectionist mechanisms like diffusion and positional mechanisms like social roles. Overall, the document serves as a high-level introduction to social network concepts and their application to health research.
Introduction to Social Network AnalysisPatti Anklam
This document provides an overview of network analysis and its applications. It discusses the origins and history of network study in fields like graph theory and sociology. Various network patterns and metrics are described, including density, distance, centrality, and structural measures. Case studies are presented on using network analysis to understand expertise management, trust, and performance issues in organizations. The document emphasizes that network analysis can provide insights through metrics and visualization to inform important business and organizational questions.
Power no longer resides exclusively (if at all) in states, institutions, or large corporations. It is located in the networks that structure society. Social network analysis seeks to understand networks and their participants and has two main focuses: the actors and the relationships between them in a specific social context.
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.
Subscriber Churn Prediction Model using Social Network Analysis In Telecommun...BAINIDA
Subscriber Churn Prediction Model using Social Network Analysis In Telecommunication Industry โดย เชษฐพงศ์ ปัญญาชนกุล อาจารย์ ดร. อานนท์ ศักดิ์วรวิชญ์
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Social Network Analysis & an Introduction to ToolsPatti Anklam
This document provides an introduction to social network analysis. It discusses how networks can be mapped and analyzed using tools to understand their structure and flow of information. Key aspects of network analysis are introduced, including nodes, ties, centrality metrics, and structural patterns. A variety of tools are presented, ranging from free social media applications to specialized software, that can be used to map and analyze networks. The value of network analysis is in identifying influential individuals, improving collaboration and knowledge sharing, and intervening to change network structures and behaviors.
An interactive presentation on social network theory and analysis. Content includes information on tie formation and social capital. Network relations are explained by using the example of The A Team. Granovetter's Strength of Weak Ties Theory (1973) is also covered and weak ties and strong ties are explained. Appropriate application of social network theory to individuals understanding how to best take advantage of social networking platforms to find jobs as well as companies taking advantage of social media platforms to find followers are introduced.
Small Worlds of Ambridge: Power, Networks & Actants Nicola Headlam
Seeking to explore the ways in which multi-dimensional power may be deployed within a spatially defined place needs an interrogation of place-based statecraft. The paper presents some of the forms of capital in play in Ambridge mapped using Social Network Analysis (SNA) It argues that the extant matriarchal structure of Aldridges/Archers can be challenged by Kinship structures emphasising the weak ties, or hinges between the major cliques/clans and that within the knowledge economy Ed's multiple contractual connections make him 'King of Ambridge'
The document discusses the "querelle" or debate between network science and the new social physics. It notes that the new social physics revisited ideas like small world theory and identified networks exhibiting "small worldliness," but were criticized for lacking sociological perspective. Watts argued small world networks can emerge from random ties between nodes, but others like Granovetter and Barabasi showed real networks have non-random structures. The document argues the small world thinkers overlook sociological factors like meaning, social relations, and inequality. It notes a problem for sociology of science as the physicists do not cite foundational work in social network analysis.
Social Network Analysis: What It Is, Why We Should Care, and What We Can Lear...Xiaohan Zeng
This document provides an overview of social network analysis, including what social networks are, what can be learned from analyzing social networks, and how social network analysis can be performed. Some key findings that can be uncovered include the six degrees of separation principle, the 80-20 rule of social popularity where a minority of nodes have most connections, how to identify influential nodes, and how to group similar nodes into communities. Various metrics and models are described for analyzing features like path lengths, degree distributions, ranking nodes, measuring community structure, and more. Examples of social network analysis are also provided.
This workshop will introduce some of the main principles and techniques of Social Network Analysis (SNA). We will use examples from organizational and social media-based networks to understand concepts such as network density, diameter, centrality measures, community detection algorithms, etc. The session will also introduce Gephi, a popular program for SNA. Gephi is a free and open-source tool that is available for both Mac and PC computers.
By the end of the session, you will develop a general understanding of what SNA is, what research questions it can help you answer, and how it can be applied to your own research. You will also learn how to use Gephi to visualize and examine networks using various layout and community detection algorithms.
Instructor’s Bio: Dr. Anatoliy Gruzd is a Canada Research Chair in Social Media Data Stewardship, Associate Professor at the Ted Rogers School of Management at Ryerson University, and Director of Research at the Social Media Lab. Anatoliy is also a Member of the Royal Society of Canada’s College of New Scholars, Artists and Scientists; a co-editor of a multidisciplinary journal on Big Data and Society; and a founding co-chair of the International Conference on Social Media and Society. His research initiatives explore how social media platforms are changing the ways in which people and organizations communicate, collaborate and disseminate information and how these changes impact the norms and structures of modern society.
This document provides 25 potential essay questions for a theory and methods course in sociology. The questions assess various sociological theories and perspectives, such as structuralism, functionalism, conflict theory, feminism, postmodernism, and evaluate debates around objectivity, value-freeness, and the scientific status of sociology. Additional questions address research methods like participant observation, surveys, interviews and use of quantitative vs qualitative data.
This document outlines the key concepts and lessons for Unit 1 of a sociology course. The unit will examine the foundations and origins of sociology, the three major theoretical perspectives in sociology, and how sociological research is conducted. Students will learn about the development of sociology as an academic discipline in response to social changes in Europe. They will also explore the functionalist, conflict, and interactionist perspectives and how sociologists use various methods like surveys, experiments, and observation to study social phenomena scientifically.
This document provides an overview of the first unit in a sociology course. It includes information about the first day of class procedures and an outline of topics to be covered in Unit 1. The unit will focus on examining social life, the development of sociology, modern sociological perspectives, and conducting sociological research. Students will learn about the origins of sociology, the three major theoretical perspectives (functionalism, conflict theory, and symbolic interactionism), and how sociological research follows the scientific method and ethical guidelines.
This document provides an overview of the first unit of a sociology course. It includes:
- An introduction to examining social life, including defining sociology and differentiating it from other social sciences.
- An outline of the development of sociology from the 17th-19th centuries in Europe in response to industrialization and other social changes. Key early theorists who contributed to the field are identified.
- An introduction to the three major theoretical perspectives in sociology - functionalism, conflict theory, and symbolic interactionism - and how they differ in their levels of analysis.
- An overview of how sociological research is conducted scientifically, using methods like surveys, observation, and experiments while following ethical standards
The document discusses several dominant approaches in the social sciences including:
1) Microlevel approaches like rational choice theory and symbolic interactionism that focus on individual behavior.
2) Macrolevel approaches like structural functionalism and institutionalism that examine larger social systems and structures.
3) Interdisciplinary approaches such as the human-environment system that integrate ideas across fields.
It then provides more details on specific theories under the microlevel and macrolevel categories.
This document discusses several dominant approaches and ideas in the social sciences. It outlines microlevel approaches like rational choice theory and symbolic interactionism, which focus on individual behavior and decision-making. It also discusses macrolevel approaches like structural functionalism and institutionalism, which examine larger social systems and structures. Structural functionalism views society as a complex system whose parts work together to promote stability. Institutionalism studies how formal and informal institutions influence social behavior by constraining and empowering individuals. The document provides overviews of the key concepts and premises of these different theoretical perspectives in social science.
Symbolic Interactionism, Structural-Functional Theory and Conflict Theory Vijayalakshmi Murugesan
This document provides an overview of three major sociological theories: symbolic interactionism, structural-functional theory, and conflict theory. Symbolic interactionism examines how individuals construct meanings through interactions and symbols. Structural-functional theory views society as a system of interrelated parts that work together to maintain stability. Conflict theory sees society as groups competing for limited resources and views social institutions as maintaining inequality between groups.
These slides are for my talk for the Somerville College Mathematics Reunion ("Somerville Maths Reunion", 6/24/17): http://www.some.ox.ac.uk/event/somerville-maths-reunion/
Talcott Parsons was an American sociologist who developed structural functionalism, which views society as a system of interconnected parts that work together to maintain stability and social order. Parsons was influenced by theorists like Durkheim, Weber, Spencer, and Comte. He developed theories of social action, the social system, AGIL functions, and pattern variables. Parsons viewed society as made up of interdependent institutions that help society adapt, attain goals, integrate, and maintain social order. He believed rapid social change could disrupt this equilibrium.
This document provides an agenda for a class on social media that includes discussions on various social media terms and concepts. It outlines activities for students, such as defining social media and discussing the differences between social media "visitors" and "residents". It also lists various readings and resources for students to explore key topics in social media research, such as network analysis, tie strength, and strategic planning for social media initiatives. The document provides links to external resources and materials to support the activities and assignments for the class.
This document provides an overview of sociology as a field of study. It defines sociology as the systematic study of human society and social behavior, from large institutions to small groups. It discusses key concepts like social behavior, society, and the sociological perspective. It also outlines some of the main topics studied in sociology like socialization, culture, groups, inequality, and social institutions. The document emphasizes the importance of developing a sociological imagination to understand how individual experiences are shaped by broader social and historical forces.
This document provides an overview of sociology as a field of study. It defines sociology as the systematic study of human society and social behavior, from large institutions to small groups. It discusses key concepts like social behavior, society, and the sociological perspective. It also summarizes some of the main topics covered in sociology like socialization, culture, groups, inequality, and social institutions. The document emphasizes that sociologists study people and society objectively using methods like participant observation, surveys, and the scientific method to collect both quantitative and qualitative data.
This document provides an overview of sociological theories and research methods. It introduces some key modern sociological paradigms including structural functionalism, conflict theory, and symbolic interactionism. It also discusses newer approaches such as feminist theory, queer theory, and postmodern theory. Finally, it outlines some common social science research methods for studying society, including ethnography, interviews, surveys, experiments, and the scientific method. The goal is to help students understand how sociological theories develop and change over time and the tools used to study society.
The document provides an overview of the field of sociology. It discusses key concepts in sociology like examining general patterns of behavior across social groups and how society shapes individual experiences. It also outlines several subfields of sociology such as family, education, work, health, and religion. The origins and early founders of sociology are presented, with Auguste Comte cited as coining the term in the 1830s. Important research methods in sociology like surveys, experiments, and participant observation are summarized.
The document discusses three major theoretical perspectives in sociology: symbolic interactionism, functionalism, and conflict theory. It provides details on the key concepts and assumptions of each perspective. Symbolic interactionism focuses on symbols and social interactions. Functionalism views society as a system of interdependent parts that work together. Conflict theory emphasizes social change and competition over scarce resources between groups in society. The document also notes criticisms of each perspective.
This document discusses the theoretical foundations of sociology. It outlines three major sociological perspectives: symbolic interactionism, functionalism, and conflict theory. Symbolic interactionism focuses on symbols and social interactions on a micro level. Functionalism views society as a system whose parts work together to promote solidarity and stability. It examines the functions of social institutions on a macro level. Conflict theory emphasizes competition and power struggles in society, especially between social classes.
Structural Sociologists Vs Interpretive Sociologists EssayMichelle Love
Structural sociologists and interpretive sociologists use different research methods depending on their theoretical positions. Structural sociologists model their work on natural sciences and seek quantifiable data using methods like experiments and questionnaires. Interpretive sociologists focus on meanings and definitions to understand behavior, using qualitative methods like interviews and participant observation. Both approaches have advantages and limitations depending on the situation.
Sociology is the scientific study of society, human social behavior, and the organization of human social interaction. The document outlines the key founders of sociology in the 19th century and their contributions to establishing it as a science. It also summarizes major areas of focus in sociology such as macro and micro levels of analysis, key theoretical paradigms, and common research methods used by sociologists like surveys, experiments, and participant observation.
Sociology is the scientific study of society, human social behavior, and the organization of human social interaction. The document outlines the key founders of sociology in the 19th century and their contributions to establishing it as a science. It also summarizes major areas of focus in sociology such as macro and micro levels of analysis, key theoretical paradigms, and common research methods used by sociologists like surveys, experiments, and participant observation.
This document summarizes research on interlocking directorates, which are instances where members of one company's board also serve on other companies' boards. Key findings include:
- Early 20th century studies found extensive interlocking between large US banks and corporations, leading to antitrust laws prohibiting competing firms from having interlocking boards.
- More recent network analysis finds the number of interlocks has declined in some countries but increased in others over time. Financial institutions typically have the most interlocks.
- Qualitative studies provide insights into how interlocks facilitate communication and coordination between firms while also concentrating power and control among elite members who serve on multiple boards.
- Future research opportunities include longitudinal analysis of international networks
This document provides an overview of using social network analysis to study cultural production. It discusses how the Manchester punk/post-punk music scene from 1976-1980 formed a cultural network among over 100 key actors. Having a "critical mass" of interconnected artists allowed resources and enthusiasm to be pooled, cultural work to be completed, and a music scene to emerge and be recognized. The network structure influenced opportunities for collaboration, support, and innovation. Studying relationships and dynamics within cultural networks can provide insights into how conventions, resources, and opportunities are distributed and how cultural production unfolds over time.
This document summarizes a study that analyzed the social networks of scientists working in the field of agricultural innovation. The study used social network analysis techniques to examine:
- The communication and collaboration ties between scientists in the field to understand if an "invisible college" existed.
- How productive scientists were more central in the network than others based on measures like degree and density.
- How the field grew over time, with most new entrants in the late 1950s and early 1960s, including many students of the most productive scientists.
- How scientists could be grouped into distinct collaborative subgroups within the overall network based on their coauthorships and student-advisor relationships.
1) The study defined three categories of injecting drug users (IDUs) in a neighborhood in New York - a core network of 40 IDUs, an inner periphery of 95 IDUs who obtained drugs and assistance from the core, and an outer periphery who purchased drugs independently without interacting with the core.
2) Data was collected through ethnographic observation of hundreds of drug users, 210 interviews, and structured interviews with 767 IDUs where they named their injection partners.
3) Different levels of HIV risk behaviors and infection rates were found among the three network groups, with the core having the highest rates.
This document summarizes several studies on the diffusion of innovations across social networks. Key points:
1. Early studies examined how individual attributes like age and social attributes like social ties affected the timing of adoption of a new drug. Doctors who were more socially integrated adopted the drug earlier.
2. Later studies analyzed longitudinal data to map the spread of behaviors like smoking across social networks over time. Clusters of adopters extended to three degrees of separation and friends, siblings, and spouses influenced each other's adoption rates.
3. Threshold models propose individuals adopt based on a threshold proportion of their social network already adopting. Those with low thresholds adopt early while those with high thresholds adopt later. This personal network approach
This document summarizes key concepts and theorists related to social capital. It discusses the work of Pierre Bourdieu, James Coleman, and Robert Putnam, who view social capital as the advantages generated by social networks and relationships. It also covers network perspectives that focus on measuring individuals' social ties and potential access to resources. The document outlines theories of social capital and studies that have tested relationships between social networks, accessed and mobilized social capital, and socioeconomic outcomes.
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Azure Interview Questions and Answers PDF By ScholarHat
Lecture 1
1. TODAY
• Lecture 1 part 1 (40 mins).
What is social network analysis? Brief history
• Tutorial 1 (30 mins)
Organization of groups and selection of topics
• Lecture 1 part 2 (40 mins)
Data collection
• Workshop 1 (30 mins)
• Facebook demonstration (10 mins)
2. LECTURE 1: PART 1
Why study networks?
Many phenomena seem to be structured as networks:
- Neural networks
- Circulatory systems
- Organizations
- Economies
- Ecologies
- …
An actor’s position in a network shapes opportunities and constrains, and may be able to
predict outcomes of her behaviour.
What happens to people an actor is connected to may influence her own behaviour as well
Eg: I want to sell my product in china, I need a Chinese contact who introduces me to the
market.
Eg: I want to get involved in a student political movement to support gay marriage, but my
parents are strongly against it
Eg: all my friends have bought an iphone, it is more likely that I
will buy one as well
3. Relationships among entities.
- Social and inanimate
- Individual and collective
What are networks?
Egonetworks
Whole networks
DEPENDENCIES
Actors and attributes
• Categorical (male/female)
• Continuous (56 year old)
• Ordinal (low class/middle class/upper class)
Relationships
• Multiple (being married, being coworkers, living together)
• Valued (continuous, having known each
other for 56 years, or ordered, like
exchanging emails once a week, every
month)
• Directed
• Indirect connections (chains and paths)
4. What are relations?
What are the differences between relational status and events?
Each tie gives a corresponding network. Multiple ties produce multiple networks (friendship,
advises, etc.)
Relational states: continuous and persistent relationships
Relational events: discrete events
States:
• Similarities: antecedents and consequences of social ties, occasions
• Roles: permanent relations
• Cognition: thought and feelings people have of each other, not directly observable, but
inferred from interaction or directly asked to people
Events:
• Interaction: observable behaviours between two people
• Flow: outcomes of interactions, tangible (money) and intangible(information, beliefs)
Similarities
Location
Same
spatial and
temporal
space
Participation
Same clubs,
same events
Relational
states
Relational roles
Other
Attribute
Kinship
Role
Same
gender,
same
attitude
Mother
of, sibling
of
Friend of,
boss of,
student
of,
competit
or
Relational events
Relational cognition
Percep-t
Affective
ual
Likes,
hates
Knows,
knows of,
sees as
happy
Interactions
Sold to,
talked
to,
helped,
fought
with
Flows
Informati
on,
beliefs,
money
5. What is the goal of network analysis?
Network variables as independent/explanatory: network processes are used to explain and
predict outcomes.
- Brokers may have advantages
- Closure my be restraining
- Centrality may produce stress
Network variables as dependent/outcomes:
- Homophily may explain relationship formation
Network variables as independent/explanatory
Network variables as dependent/outcomes
Friendship between pairs of farmers to predict
Dyad level which pairs of farmers make the same decision
about going organic
Similarity of interests (e.g., sky diving) to
predict who becomes friends with each other
Centrality in organizational trust network to
Node level predict who is chosen for promotion
Extraversion to predict who becomes central
in friendship network
Shortness of paths in a group’s communication
Network level network to predict group’s ability to solve
problems
Type of organizational culture (emphasizing
either cooperation or competition) to predict
structure of the trust network
6. Brief history of SNA
See:
Freeman L. C., 2004, The development of social network analysis, Empirical Press,
Vancouver.
Prell C., 2012, Social Network Analysis. History, theory and methodology, Sage, London.
Chapter 2: 19-52.
SNA emerged out from
- Psychology
- Social anthropology
- Sociology
But since the origin it was interdisciplinary: Elizabeth Both first anthropologist, then
psychologist; Mayo (psychology) and Warner (social anthropology)
7. Psychology
• Jacob Moreno
Student of psychiatry in Vienna, then moved to US in 1925 and developed sociometry (30s)
How social relations affect psychological well being. Sociograms are visual depictions of
individuals and their relationships. Sociometry faded in the 50s: frustration for the
difficulties in uncovering meaningful patters when networks reach a certain size.
In the 40s, mathematicians started using matrices and graph theory to meet this demand.
• Kurtin Lewin
He similarly studied Gestalt theory (vs behaviourists) and moved to US in 1930s. In 1945 he
became the director of the Research Centre for Group Dynamics, MIT.
Field theory: the totality of coexisting facts which are conceived of as mutually
interdependent.
8. Psychology
• Alex Bavelas
Student of Lewin, and director of the Group Networks Laboratory (at MIT, from Lewin
centre). They began studying the effects of different communication network structures on
the speed and accuracy with which a group could solve problems.
Development of the concept of centrality: central
actors are optimally positioned for integrating
Information from dislocated parts of the network.
Centralization as a global measure
• Luce and Perry, and the concept of clique
9. Psychology
• Festinger, Cartwright and Harary
Second centre to spring out of MIT, at University of Michigan (50s). Collaboration with UK
(1947). Through the journal Human relations influence over E. Bott
• Balance theory from Heider:
they re-defined it in structural terms using graph
theory, extending it from individual cognitive states
to any social phenomena that could be represented
in network terms.
•
-
Current psychological work:
Social influence
Homophily
Social exchange theory
10. Social Anthropology
• Radcliffe Brown
UK, Australia, Chicago, Oxford with Gluckman, etc.
Structuralist, but with more emphasis on social relations that structural functionalism.
Networks can help to move beyond abstract concepts (reifications) of culture and class.
• Lloyd Warner
Student of Radcliffe Brown who moved to Harvard and worked with Mayo to the research
at the Western Electric Company and at the Hawthorne factory.
Yankee city study, anthropological study of a urban setting.
In Chicago Deep South, on the impact of race differences on social stratification (2 mode
Davis data).
11. Social Anthropology
• Max Gluckman
First chair of Manchester’s dept. of social anthropology and sociology
50s and 60s: Manchester school.
Study of social networks in natural settings, cross cutting ties in the development of
conflicts.
• James Clyde Mitchell
British sociologist who followed Gluckman in Manchester in 1965 as Chair in Urban Studies.
Clyde was interested in the study of social structure through the observation of regular
patterns of social relations that persist over time. Social networks as an opportunity to mix
the qualitative and thick descriptions of the cultural peculiarities of structural environments
with a “non-quantitative mathematical way of rigorously stating the implications entailed in
a set of relationships” (Mitchell 1969: 1).
12. Social Anthropology
London School of Economics
• Elizabeth Bott
Many contacts with the Manchester school.
Married couples and personal networks.
Density
• John Barnes
Bott’s colleague, and the first one to use the term social networks in a fiend study
• Siegfrid Nadel
Role analysis
MIXED METHODS APPROACH
13. Sociology
• Simmel:
- dyads and triads
- differentiation of social circles
Peculiarities of urban societies in relation not only to the increase in the population size, but
in the consequential differentiation of social circles where the structure of social relations is
organised in multiple, sparse and partially overlapping clusters.
• References to the fundamental role of interconnections as irreducible elements of social
life can be found across a vast range of thinkers like Marx, Tönnies, Spencer, Weber,
Durkheim.
• Pareto: elites are constantly reproduced by individuals and their investment in
relationships
• Harvard: interest in Pareto, Warner, Parsons, Merton, Mayo. Mayo supervises Homans.
Homans develops a theory of social relations and social groups. Small group research (50s)
14. Sociology
At the same time of Homans, Merton was at Harvard, who lately trained Coleman, Blau,
Kadushin.
• Coleman
Diffusion and social capital
• Kadushin
Simmel’s social circles
• Blau moved to Columbia, and trained Davis
Clustering
Transitivity
Triad census (Holland and Leinhardt)
15. Sociology
At Harvard in the 70s
Harrison White
Maths, physics and sociology.
Chains of opportunity applies algebraic models to the study of the job market.
Whole networks VS egonets (Manchester school)
Block modelling and positional analysis
Among his students:
Granovetter
Bonacich (centrality measures)
Wellman
16. The Mitchell Centre
• Established in 2009
• Nick Crossley, Martin Everett, Gemma Edwards, Elisa Bellotti, Susan
O’Shea, Kathryn Oliver, Mark Tranmer (CCSR), Johan Koskinen
(CCSR)
• Interests in social movements, covert networks, music networks,
scientific networks, personal networks, health networks, interorganizational networks…
• Mixed methods, development of methods for one mode and two
mode networks, multilevel analysis, network modelling, and
network dynamics
19. LECTURE 1: PART 2
Data collection
Marsden P. V., 1990, Network data and measurement, Annual Review of Sociology, 16: 435463.
Social structures as patterns of specifiable relations of social units. Social structures place
opportunities and constrains on individual action according to one’s position.
Opportunities: social resources, social capital, social support.
Distinction between:
1. Existing social relations: important for diffusion mechanisms/Perceived networks
(cognitive): importance for social influence on attitudes and opinions
2. Momentary reactions/Routinised and recurrent relationships
20. Boundaries specifications
Focus on interdependencies, therefore the omission of nodes (and relationships) would
alter the overall structure
Realist approach: subjective perception of actors who belong to the network
Nominalist approach: observer standpoint
Egonets:
• star, first zone, second zone
• Unlimited VS limited number of alters
• Type of ties
• Alter’s roles and attributes
• Normal sampling
Whole networks
• Membership criteria (roster method)
• Snowball
• Participation (eg: events)
21. How to collect data
• Name generator (egonet and whole net). Ego attributes, ego-alter
ties, alter attributes, alter-alter ties
• Position generator (egonet). Ego attributes, frequency of egoalter ties (with no names), alter ties attributes
• Resource generator (egonet), Ego attributes, frequency of egoalter ties (with no names), alter ties attributes
Data collected via
• Surveys
• Qualitative interviews
• Ethnographic observations
• Archival data
22. Name generator
Can be used for egonetworks as well as whole networks.
Question
Answer
Data
-Who did you discuss matters
important to you in the last 3
months?
John
Jack
Bob
Ego
John
Jack
Bob
-Who did you ask for advice in the
past 3 months?
John 2 times
Jack 3 times
Bob 1 time
Ego
John
Jack
Bob
-Who has lent you money?
Bob 15000£
Jack 10000£
Ego
John
Jack
Bob
-Who would you discuss matters
important to you with?
-Who did you lend money to?
John 25000£
23. Who did you lend money to?
Who did you borrow money from?
How much?
How much?
25000
0
Bob
0
15000
Jack
0
10000
John
….
Alters’ atttributes
Who did lend money to who, of
which you are aware?
John
Bob
Jack
0
5000
3000
Bob
2500
0
0
Jack
0
7000
0
John
Gender
Age
No. Of kids
John
1
50
3
Bob
1
46
0
Jack
1
72
2
24. Adjacency Matrices
Binary
Jim
Jim Jill 1
Jen 0
Joe 1
Jill Jen Joe
1 0
1
- 1
0
1
1
0 1
-
Jill
Jen
1
3
Jim
9
Valued
Jim
Jim Jill 3
Jen 9
Joe 2
Jill Jen Joe
3 9
2
- 1 15
1
3
15 3
-
3
15
2
Joe
25. Directed vs undirected ties
• Undirected relations
– Attended meeting with
– Communicates daily with
• Directed relations
– Lent money to
• Logically vs empirically directed ties
– Empirically, even undirected relations can
be non-symmetric due to
measurement error
Bonnie
Bob
Biff
Betty
Betsy
26. Position generator
Do you know anyone
who is a/an
U&S2
ISEI3
acq.
% yes
family
member
friend
lawyer
86
83
47
40
25
35
doctor
84
87
50
41
19
40
policymaker
82
70
45
33
28
39
engineer
76
68
65
24
21
56
informationtechnologist
68
70
66
30
27
42
manager
67
69
66
21
27
52
directorcompany
67
69
71
24
24
52
tradeunionmanager
66
65
17
57
20
23
scientist
65
71
42
26
28
46
highercivilservant
64
61
53
35
21
44
Source: Position Generator measures and their relationship
to other Social Capital measures
Martin Van der Gaag, Tom A.B. Snijders, Henk D. Flap
http://www.xs4all.nl/~gaag/work/PG_comparison.pdf
27. Resources generator
Source: Position Generator measures and their
relationship to other Social Capital measures
Martin Van der Gaag, Tom A.B. Snijders, Henk D. Flap
http://www.xs4all.nl/~gaag/work/PG_comparison.pdf
28. Roster method (whole networks)
Everyone belonging to the network has to fill in the questionnaire
Here there is the list of people who
work in your office
WIthin them, who do you
ask for advice?
Bill
2
Joe
0
Anna
0
Carol
1
29. Surveys
Realist approach: they elicit ego’s subjective perception of actors who belong to his/her
network.
They can focus on
• the content of exchange between people, by asking whom ego discuss important
matters with, or socialise (exchange approach)
• the role of the relationship, by asking to list friends, neighbours, co-workers, and the
like (role-relational approach)
• the strength of the relation, but asking whom ego feels especially close to (affective
approach)
• the frequency of communication, by asking whom ego is in contact with (how often,
via which media) over a certain period of time (interactional approach)
• the locality of ties, by asking who lives nearby or in the same geographical area
(geographical approach).
30. Surveys
• Laumann (1973): in 1965 surveyed 1013 native-born, white men, between the ages of
21 and 64, in the greater metropolitan area of Detroit, asking them about three closest
network members.
• Wellman (1993): designed the sociological component of a series of East York studies.
Large study administered in 1967 and 1968. Survey of 845 respondents, to whom he
asked the names of all the people living in their household, and the initials of the
people outside the household that they feel closest to. The name generator asked only
the about the first six people, but also added the information on how many they feel
close to on top of these 6 (if any), which gives an approximation of the size of the
network. Together with the list of names, Wellman also used name and ties
interpreted, asking a wide range of alters’ attributes (role, sex, occupation, where they
live) and the frequency, mean, and reason for contacts (how often they are seen, how
often they are contacted by phone or letter, who they get together with informally,
who provides help for everyday matters or in case of emergencies). Finally, alter-alter
ties are collected.
31. Surveys
• Fischer (1982a), in his study of personal networks in 50 urban and rural Northern
California communities, surveyed 1050 adults about their exchange of support
(emotional companionship, material). He uses 10 different name generators and 19
name and tie interpreters. 8 of those interpreters are asked for all the names elicited,
while 11 (gaining details about how long they have been known by ego, the frequency
of contact, how they were met) are asked only for the first five alters named. For each
pair of names he also asks if they know each other well, obtaining alter-alter ties.
• Burt (1984)Items for the US General Survey Election. Only one name generator is used
that elicits names of people ego discussed personal matters during the previous six
months. While no size boundaries are adopted, name interpreters are asked only for
the first 5 people named, for whom a 3 grades strength of alter alter-ties is also
administered. The strength of ego-alter ties is operationalized as especially close VS
moderately close, frequency of contacts, years of acquaintance, relationship content
(discussion topics), and role (kin, friend, etc.).
32. Visually aided data collection
Visualization is very common in social network analysis, but it is more often used in the
analysis rather than in the collection of data
• Fizgerald (1978) used a creative process for collecting relational information in Africa,
where she asked her respondents to write names of alters on plastic chips and to
arrange them according to the strength of the tie.
• Commonly used is the target, which consist in a series of concentric circles where ego
stands in the middle, and has to place the names of alters alongside the circles,
following the guideline that the nearer to the centre the closest the relationship. This
tool has been originally designed by Kahn and Antonucci (1980) and recently adopted,
for example, by Spencer and Pahl (2006) in their study of friendship. No alter-alter ties
33. Qualitative interviews
Realist approach
Qualitative interviews in network research are not used differently from any other
qualitative study, insomuch as they can take the form of semi-structured interviews, indepth interviews, thematic interviews, or life histories. However, when adopted in the
investigation of networks they normally aim at exploring the content of relationships, and
the meaning of the overall structure of individual social environments.
Mostly used in egonets, rarely in whole nets
By recording the subjective accounts of network structures, they aim to gain an insider
view of the interactional processes which generate those structures (Edwards 2010).
Already in East York study
34. Qualitative interviews
• Bidart and Lavenu (2005) interviewed 66 young people living originally in Normandy
(France), who were questioned every three years about the evolution of their personal
networks and the events marking their entry into adult life.
• Hollstein (forthcoming) combines fuzzy set analysis of qualitative material and network
data to investigate youth transition from school to work.
• Bellotti (2008a; 2008b) interviewed 23 single young adults living in Milan (Italy) about
the composition, dynamics and outcomes of their friendship networks.
• Bernardi et al. (2007) interviewed 64 young adults living in two cities in Germany in
order to investigate the social mechanisms at work or the variation in the composition
of the networks of informal relationships in relation to fertility behaviour.
35. Ethnographic observations
More common for whole nets
• Department of Social Anthropology and Sociology at the University of Manchester
mostly focussed on the use of observations for the mapping of interactions in various
settings.
• Epstein for the study of the spread of gossip (Epstein 1969a and 1969b)
• Kapferer used observations to map interactions between a group of African mine
employees who were engaged in surface work in the Cell Room of the Electro-Zinc
Plant of the mine (Kapferer 1969: 184).
• Wheeldon (1969) studied a coloured community in Southern Africa, focussing the
attention on six leaders who were frequently named by other members of the
community
• Boswell (1969) observed the mobilization of personal networks during periods of crisis
in the African city of Lusaka
Clyde Mitchell, 1969, (ed.), Social Networks in urban
situations, Manchester University Press, Manchester.
36. Ethnographic observations
• Studies mapped concrete interactions in a group of deaf teletype users, between
amateur radio operators, in a small social science research firm, and participants of a
university graduate program (Bernard and Killworth 1977)
• Observation of interactions between drug users (Curtis et al. 1995)
• Relationships between students, teachers, and parents in school classrooms (Haussling
2010)
• Conversational interactions and speaking turns in meetings of managers (Gibson 2005)
• Ethnographic studies of hidden populations (Schensul et al. 1999)
• Classic study of an Italian slum in Chicago (Whyte 1943), shadowing an egonet
• Similar to observations are diaries
37. Archival data
Whole net and egonet
information is not created for the purpose of the research, but pre-exist the data
collection process: this means that the researcher has a minimal influence in the
production of the data, especially compared to other form of direct inquiry like surveys
and interviews.
Nominalist approach: data selected independently from actors’ perceptions, and
according to the researcher’s goals
• Interlocking directorates
• Padgett and Ansell (1993): structure of relationships between oligarchic families in
Florence during Renaissance.
• Crossley on the development of the punk scene in London (Crossley 2008b) and
Manchester (Crossley 2009)
• Analysis of the structural advantages in obtaining funding in academic disciplines
(Bellotti 2012; forthcoming).
• Edward and Crossley on the egonetwork of the suffragette Helen Kirkpatrick Watts
(Edward and Crossley 2009).
38. RECAP
• SNA as a way to formalise relational structures and dependencies between actors. Nodes
and ties to visualise networks.
• Various types of nodes, and various types of relations
• SNA interdisciplinary. Psychology, social anthropology and sociology paths, all combined
with mathematics.
• Egonet ad whole nets
• Boundaries specifications in both approaches
• Nominalist VS realist approach
• Name generator
• Position generator
• Resource generator
•
•
•
•
Survey
Interviews
Observations
Archival data
39. References
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Bellotti E., Qualitative networks. Mixing methods in social research, Routledge, London, forthcoming.
Bellotti, E., 2008a. What are friends for? Elective communities of single people, in Social Networks, 30, 318-329.
Bellotti, E., 2008b. Amicizie. Le reti social dei giovani single, Milano, F. Angeli.
Bernard R. H. and P. D. Killworth. 1977 Informant Accuracy in Social Network Data II. Human Communications Research
4:3–18.
Bernard, H. R., E. C. Johnsen, P. D. Killworth, C. McCarty, G. A. Shelley, and S. Robinson. 1990. Comparing four different
methods for measuring personal social networks. Social Networks 12 (3): 179–215.
Bernardi L., Keim S., von der Lippe H., 2007, Social Influences on Fertility: A Comparative Mixed Methods Study in
Eastern and Western Germany, Journal of Mixed Methods Research, 1, 1, 23 – 47.
Bidart C. e Lavenu D. (2005), «Evolution of personal networks and life events» in Social Networks, 27, pp. 359 – 376.
Borgatti S.P., Mehra A., Brass D.J., Labianca G., 2009, Network Analysis in the Social Sciences, Science, 13, 323, 5916:
892-895.
Brandes U., Robins G., McCranie A., Wasserman S., 2013, What is network science?, Network Science, 1, 1: 1-15.
Burt R., 1984, Network items and the general social survey, Social Networks, 6, 293 – 339.
Crossley, N. (2009) ‘The Man Whose Web Expanded: Network Dynamics in Manchester’s Post-Punk Music Scene 19761980’, Poetics 37(1), 24-49.
Crossley, N. 2008b “Pretty Connected: the Social Network of the Early UK Punk Movement.” Theory, Culture and
Society 25, 6: 89-116.
Curtis R, Friedman S, Neaigus A, Jose B, Goldstein M, Ildefonso G. Street level markets: network structure and HIV risk.
Social Networks. 1995;17:229–249.
Edwards, G. and Crossley, N. (2009) ‘Measures and Meanings: Exploring the Ego-Net of Helen Kirkpatrick Watts,
Militant Suffragette’, Methodological Innovations On-Line 4: 7-61.
Edwards, G., 2010. Mixed-Method Approaches to Social Network Analysis. Review paper, ESRC National Centre for
Research Methods.
Fischer, C.S., 1982a. To Dwell Among Friends. Personal Networks in Town and City. The University of Chicago Press,
Chicago and London.
40. References
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Fitzgerald, M. 1978. The content and structure of friendship: An analysis of the friendships of urban Cameroonians.
Unpublished doctoral dissertation, Department of Anthropology, University of Toronto.
Freeman L. C., 2004, The development of social network analysis, Empirical Press, Vancouver.
Gibson D., 2005, Taking Turns and Talking Ties: Networks and Conversational Interaction, AJS 110 6: 1561–97
Häussling R., 2010, Allocation to Social Positions in Class : Interactions and Relationships in First Grade School Classes
and Their Consequences, Current Sociology 58, 1: 119 – 138.
Hollstein B., Fuzzy Set Analysis of Network Data as Mixed Method. Personal Networks and the Transition from School
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