The average of many people trust online comments for any news as much as personal recommendations [1], [2].
In this paper, we analyzed the impact of the online news’s comments to evaluating the threading models of
electronic debates by using online surveys. In this paper, based on the results of our online survey of 500
participants, we evaluated whether forums with comments concerning online news are appropriate for the study
of debates. In particular, we have to verify whether the nature of discussions around news is argumentative and
whether the participating people expect to engage in multiple rounds of arguments. We presented
DirectDemocracyP2P application as a user interface for decentralized debates. In this paper, we evaluated and
analyzed the comments that were collected from online surveys to improve the DirectDemocracyP2P
applications. Also we have to verify whether the actual comments commonly submitted around news do go
beyond the simple advertisement of one own’s merchandise and attacks of competitors, into fair reviews of
news features and quality.
Expectations for Electronic Debate Platforms as a Function of Application DomainIJERA Editor
Electronic debate (or commenting) platforms are used with many types of online applications, as a way to engage the users or to provide enhancements, e.g., based on some type of collaborative filtering [1], [2]. The applications enhanced with such debate platforms range widely : news, products, sport, religion, politics, etc. Therefore, the emerging question is whether it is possible to make one electronic debate mechanism good for all applications, and whether the studies on the success of a debate mechanism in one domain do automatically apply to other application domains. Here we compare two traditional application domains of electronic debate platforms: product evaluation and commented news. We exploit the fact that most users are very familiar with both types of such applications, and therefore surveys can be designed to gauge reliably subtle differences between expectations and properties of these domains. Based on over 1000 responses to surveys described here, we are able to report statistically significant differences between the user behavior and expectations in the studied domains.
Abstract: We present an online deliberation system using mutual evaluation in order to col- laboratively develop solutions. Participants submit their proposals and evaluate each other's proposals; some of them may then be invited by the system to rewrite "problematic" proposals. Two cases are discussed: a proposal supported by many, but not by a given person, who is then invited to rewrite it for making yet more acceptable; and a poorly presented but presumably interesting proposal. The first of these cases has been successfully implemented. Proposals are evalu- ated along two axes—understandability (or clarity, or, more generally, quality), and agreement. The latter is used by the system to cluster proposals according to their ideas, while the former is used both to present the best proposals on top of their clusters, and to find poorly written proposals candidates for rewriting. These functionalities may be considered as important components of a large scale online deliberation system.
H. Purohit, Y. Ruan, A. Joshi, S. Parthasarathy, A. Sheth. Understanding User-Community Engagement by Multi-faceted Features: A Case Study on Twitter. in SoME 2011 (Workshop on Social Media Engagement, in conjunction with WWW 2011), March 29, 2011.
Paper: http://knoesis.org/library/resource.php?id=1095
More on Social Media @ Kno.e.sis at http://knoesis.org/research/semweb/projects/socialmedia/
Stakeholder Engagement and Public Information Through Social Media: A Study o...Marco Bellucci
Manetti, G., Bellucci, M., & Bagnoli, L. (2016). Stakeholder Engagement and Public Information Through Social Media: A Study of Canadian and American Public Transportation Agencies. The American Review of Public Administration. doi:10.1177/0275074016649260
http://arp.sagepub.com/content/early/2016/05/13/0275074016649260.short
Recommendation System Using Social Networking ijcseit
With the proliferation of electronic commerce and knowledge economy environment both organizations and
individuals generate and consume a large amount of online information. With the huge availability of
product information on website, many times it becomes difficult for a consumer to locate item he wants to
buy. Recommendation Systems [RS] provide a solution to this. Many websites such as YouTube, e-Bay,
Amazon have come up with their own versions of Recommendation Systems. However Issues like lack of
data, changing data, changing user preferences and unpredictable items are faced by these
recommendation systems. In this paper we propose a model of Recommendation systems in e-commerce
domain which will address issues of cold start problem and change in user preference problem. Our work
proposes a novel recommendation system which incorporates user profile parameters obtained from Social
Networking website. Our proposed model SNetRS is a collaborative filtering based algorithm, which
focuses on user preferences obtained from FaceBook. We have taken domain of books to illustrate our
model.
Probabilistic Graphical Models for Credibility Analysis in Evolving Online Co...Subhabrata Mukherjee
One of the major hurdles preventing the full exploitation of information from online communities is the widespread concern regarding the quality and credibility of user-contributed content. We propose probabilistic graphical models that can leverage the joint interplay between multiple factors --- like user interactions, community dynamics, and textual content --- to automatically assess the credibility of user-contributed online information, expertise of users and their evolution with user-interpretable explanation. We devise new models based on Conditional Random Fields that enable applications such as extracting reliable side-effects of drugs from user-contributed posts in health forums, and identifying credible news articles in news forums.
Online communities are dynamic, as users join and leave, adapt to evolving trends, and mature over time. To capture this dynamics, we propose generative models based on Hidden Markov Model, Latent Dirichlet Allocation, and Brownian Motion to trace the continuous evolution of user expertise and their language model over time. This allows us to identify expert users and credible content jointly over time, improving state-of-the-art recommender systems by explicitly considering the maturity of users. This enables applications such as identifying useful product reviews, and detecting fake and anomalous reviews with limited information.
Expectations for Electronic Debate Platforms as a Function of Application DomainIJERA Editor
Electronic debate (or commenting) platforms are used with many types of online applications, as a way to engage the users or to provide enhancements, e.g., based on some type of collaborative filtering [1], [2]. The applications enhanced with such debate platforms range widely : news, products, sport, religion, politics, etc. Therefore, the emerging question is whether it is possible to make one electronic debate mechanism good for all applications, and whether the studies on the success of a debate mechanism in one domain do automatically apply to other application domains. Here we compare two traditional application domains of electronic debate platforms: product evaluation and commented news. We exploit the fact that most users are very familiar with both types of such applications, and therefore surveys can be designed to gauge reliably subtle differences between expectations and properties of these domains. Based on over 1000 responses to surveys described here, we are able to report statistically significant differences between the user behavior and expectations in the studied domains.
Abstract: We present an online deliberation system using mutual evaluation in order to col- laboratively develop solutions. Participants submit their proposals and evaluate each other's proposals; some of them may then be invited by the system to rewrite "problematic" proposals. Two cases are discussed: a proposal supported by many, but not by a given person, who is then invited to rewrite it for making yet more acceptable; and a poorly presented but presumably interesting proposal. The first of these cases has been successfully implemented. Proposals are evalu- ated along two axes—understandability (or clarity, or, more generally, quality), and agreement. The latter is used by the system to cluster proposals according to their ideas, while the former is used both to present the best proposals on top of their clusters, and to find poorly written proposals candidates for rewriting. These functionalities may be considered as important components of a large scale online deliberation system.
H. Purohit, Y. Ruan, A. Joshi, S. Parthasarathy, A. Sheth. Understanding User-Community Engagement by Multi-faceted Features: A Case Study on Twitter. in SoME 2011 (Workshop on Social Media Engagement, in conjunction with WWW 2011), March 29, 2011.
Paper: http://knoesis.org/library/resource.php?id=1095
More on Social Media @ Kno.e.sis at http://knoesis.org/research/semweb/projects/socialmedia/
Stakeholder Engagement and Public Information Through Social Media: A Study o...Marco Bellucci
Manetti, G., Bellucci, M., & Bagnoli, L. (2016). Stakeholder Engagement and Public Information Through Social Media: A Study of Canadian and American Public Transportation Agencies. The American Review of Public Administration. doi:10.1177/0275074016649260
http://arp.sagepub.com/content/early/2016/05/13/0275074016649260.short
Recommendation System Using Social Networking ijcseit
With the proliferation of electronic commerce and knowledge economy environment both organizations and
individuals generate and consume a large amount of online information. With the huge availability of
product information on website, many times it becomes difficult for a consumer to locate item he wants to
buy. Recommendation Systems [RS] provide a solution to this. Many websites such as YouTube, e-Bay,
Amazon have come up with their own versions of Recommendation Systems. However Issues like lack of
data, changing data, changing user preferences and unpredictable items are faced by these
recommendation systems. In this paper we propose a model of Recommendation systems in e-commerce
domain which will address issues of cold start problem and change in user preference problem. Our work
proposes a novel recommendation system which incorporates user profile parameters obtained from Social
Networking website. Our proposed model SNetRS is a collaborative filtering based algorithm, which
focuses on user preferences obtained from FaceBook. We have taken domain of books to illustrate our
model.
Probabilistic Graphical Models for Credibility Analysis in Evolving Online Co...Subhabrata Mukherjee
One of the major hurdles preventing the full exploitation of information from online communities is the widespread concern regarding the quality and credibility of user-contributed content. We propose probabilistic graphical models that can leverage the joint interplay between multiple factors --- like user interactions, community dynamics, and textual content --- to automatically assess the credibility of user-contributed online information, expertise of users and their evolution with user-interpretable explanation. We devise new models based on Conditional Random Fields that enable applications such as extracting reliable side-effects of drugs from user-contributed posts in health forums, and identifying credible news articles in news forums.
Online communities are dynamic, as users join and leave, adapt to evolving trends, and mature over time. To capture this dynamics, we propose generative models based on Hidden Markov Model, Latent Dirichlet Allocation, and Brownian Motion to trace the continuous evolution of user expertise and their language model over time. This allows us to identify expert users and credible content jointly over time, improving state-of-the-art recommender systems by explicitly considering the maturity of users. This enables applications such as identifying useful product reviews, and detecting fake and anomalous reviews with limited information.
SOCIAL MEDIA NEWS: MOTIVATION, PURPOSE AND USAGEijcsit
This paper presents the results of an online survey which was conducted to analyse the use of social web in
the context of daily news. Users’ motivation and habit in the news consumption were focused. Moreover,
users’ news behaviour was distinguished in three purposes such news consumption, news production and
news dissemination to find out if the usage has a passive or active character. In a second step it was
questioned which social software is used for which purpose. In conclusion users appreciate social software
for features such as interactivity and information that traditional media does not provide. Among the social
web platforms users prefer social networking sites as well as videoshare platforms. Social networking sites
also rank first in the news production and dissemination.
Twitter is going to become much less important as a person to person (peer to peer) communication medium and instead become more of a content-delivery medium like TV, where content is broadcast to a large number of followers. It's just going to become a new way to follow celebrities, corporations, and the like.
These are the findings of research by two business school professors. Their paper "Intrinsic versus Image-Related Motivations in Social Media: Why do People Contribute to Twitter?", was published in the journal Marketing Science. The professors are Olivier Toubia of Columbia Business School and Andrew T. Stephen of the University of Pittsburgh.
In Professor Toubia’s words, “Get ready for a TV-like Twitter".
The research examined the motivations behind why everyday people, with no financial incentive, contribute to Twitter.The study examined roughly 2500 non-commercial Twitter users. In a field experiment, the profs randomly selected some of those users and, through the use of other synthetic accounts, increased the selected group's followers. At first, they noticed that as the selected group's followers increased, so did the posting rate. However, when that group reached a level of stature — a moderately large amount of followers — the posting rate declined significantly.
"Users began to realize it was harder to continue to attract more followers with their current strategy, so they slowed down.When posting activity no longer leads to additional followers, people will view Twitter as a non-evolving, static structure, like TV."
Based on the analyses, the profs predict Twitter posts by everyday people will slow down, yet celebrities and commercial users will continue to post for financial gain.
The paper is attached on Slideshare.
Social network analysis for modeling & tuning social media websiteEdward B. Rockower
Social Network Analysis of a Professional Online Social Media Collaboration Community. Tuning and optimizing based on observed social network dynamics and user behavior.
In online social media platforms, users can express their ideas by posting original content or by adding comments and responses to existing posts, thus generating virtual discussions and conversations. Studying these conversations is essential for understanding the online communication behavior of users. This study proposes a novel approach to retrieve popular patterns on online conversations using network-based analysis. The analysis consists of two main stages: intent analysis and network generation. Users’ intention is detected using keyword-based categorization of posts and comments, integrated with classification through Naïve Bayes and Support Vector Machine algorithms for uncategorized comments. A continuous human-in-the-loop approach further improves the keyword-based classification. To build and understand communication patterns among the users, we build conversation graphs starting from the hierarchical structure of posts and comments, using a directed multigraph network. The experiments categorize 90% comments with 98% accuracy on a real social media dataset. The model then identifies relevant patterns in terms of shape and content; and finally determines the relevance and frequency of the patterns. Results show that the most popular online discussion patterns obtained from conversation graphs resemble real-life interactions and communication.
Design of Automated Sentiment or Opinion Discovery System to Enhance Its Perf...idescitation
In today’s social networking era, if one has to make
decision about any product, service or individual performance,
the availability of various comments, suggestions, ratings,
and feedbacks are abundant. The required decision support
data can be collected through different sources of Medias like
newspapers, blogs, and discussion forums and from internet
too. So surely, it leads to the selection of best product, service
or individual if it is analyzed efficiently. In leading and
competitive world, this is huge and practical need of industries,
organizations to empower their qualities. In the recent years,
the significant study is done in the field of sentiment analysis.
However, the earlier work focused the implementation and
evaluation of individual sub technique of sentiment analysis.
Though these implementations produces significant results
of sentiment or opinion analysis, the trust of decision makers
is still in dangling to accept the results of such analysis. In
this paper, initially, we have been described the brief review
about the sentiment or opinion analysis system. Then the
details are provided about the design and about how to build
an automated opinion discovery system to enhance
performance of sentiment or opinion analysis based on feature
extraction sentiment analysis sub technique, natural language
processing and data mining techniques in an integrated way
AN INTEGRATED RANKING ALGORITHM FOR EFFICIENT INFORMATION COMPUTING IN SOCIAL...ijwscjournal
Social networks have ensured the expanding disproportion between the face of WWW stored traditionally in search engine repositories and the actual ever changing face of Web. Exponential growth of web users and the ease with which they can upload contents on web highlights the need of content controls on material published on the web. As definition of search is changing, socially-enhanced interactive search methodologies are the need of the hour. Ranking is pivotal for efficient web search as the search performance mainly depends upon the ranking results. In this paper new integrated ranking model based on fused rank of web object based on popularity factor earned over only valid interlinks from multiple social forums is proposed. This model identifies relationships between web objects in separate social networks based on the object inheritance graph. Experimental study indicates the effectiveness of proposed Fusion based ranking algorithm in terms of better search results.
Identifying the Factors Affecting Users’ Adoption of Social NetworkingWaqas Tariq
Through the rapid expansion of information and communication technologies, social networking sites have received much more attention in the scope of internet communication. Success of a social web primarily depends on users’ satisfaction. In this context, this study aims to identify the influencing factors that affect users’ satisfaction towards social networking site use. A multidimensional model has been proposed based on the Information Quality, System Quality, Environmental and Affective dimensions to assess the effects of key variables – Semantic Intention, Usability, Web-Page Aesthetics, Subjective Norm and Trust- on users’ satisfaction. Facebook was chosen as a focused social networking site, because of its popularity. A comprehensive survey instrument was applied to 203 Facebook users. Also, Structural Equation Modeling, particularly Partial Least Square, was conducted to analyze the proposed research model. As a result, proposed multidimensional research model predicts the factors influencing users’ satisfaction towards social networking site use and relationships among these factors. The findings of this research will be valuable for literature by analyzing the influencing factors that have not been previously researched in the context of social networking satisfaction area.
Expectations for Electronic Debate Platforms as a Function of Application DomainIJERA Editor
Electronic debate (or commenting) platforms are used with many types of online applications, as a way to
engage the users or to provide enhancements, e.g., based on some type of collaborative filtering [1], [2]. The
applications enhanced with such debate platforms range widely : news, products, sport, religion, politics, etc.
Therefore, the emerging question is whether it is possible to make one electronic debate mechanism good for all
applications, and whether the studies on the success of a debate mechanism in one domain do automatically
apply to other application domains. Here we compare two traditional application domains of electronic debate
platforms: product evaluation and commented news. We exploit the fact that most users are very familiar with
both types of such applications, and therefore surveys can be designed to gauge reliably subtle differences
between expectations and properties of these domains. Based on over 1000 responses to surveys described here,
we are able to report statistically significant differences between the user behavior and expectations in the
studied domains.
SOCIAL MEDIA NEWS: MOTIVATION, PURPOSE AND USAGEijcsit
This paper presents the results of an online survey which was conducted to analyse the use of social web in
the context of daily news. Users’ motivation and habit in the news consumption were focused. Moreover,
users’ news behaviour was distinguished in three purposes such news consumption, news production and
news dissemination to find out if the usage has a passive or active character. In a second step it was
questioned which social software is used for which purpose. In conclusion users appreciate social software
for features such as interactivity and information that traditional media does not provide. Among the social
web platforms users prefer social networking sites as well as videoshare platforms. Social networking sites
also rank first in the news production and dissemination.
Twitter is going to become much less important as a person to person (peer to peer) communication medium and instead become more of a content-delivery medium like TV, where content is broadcast to a large number of followers. It's just going to become a new way to follow celebrities, corporations, and the like.
These are the findings of research by two business school professors. Their paper "Intrinsic versus Image-Related Motivations in Social Media: Why do People Contribute to Twitter?", was published in the journal Marketing Science. The professors are Olivier Toubia of Columbia Business School and Andrew T. Stephen of the University of Pittsburgh.
In Professor Toubia’s words, “Get ready for a TV-like Twitter".
The research examined the motivations behind why everyday people, with no financial incentive, contribute to Twitter.The study examined roughly 2500 non-commercial Twitter users. In a field experiment, the profs randomly selected some of those users and, through the use of other synthetic accounts, increased the selected group's followers. At first, they noticed that as the selected group's followers increased, so did the posting rate. However, when that group reached a level of stature — a moderately large amount of followers — the posting rate declined significantly.
"Users began to realize it was harder to continue to attract more followers with their current strategy, so they slowed down.When posting activity no longer leads to additional followers, people will view Twitter as a non-evolving, static structure, like TV."
Based on the analyses, the profs predict Twitter posts by everyday people will slow down, yet celebrities and commercial users will continue to post for financial gain.
The paper is attached on Slideshare.
Social network analysis for modeling & tuning social media websiteEdward B. Rockower
Social Network Analysis of a Professional Online Social Media Collaboration Community. Tuning and optimizing based on observed social network dynamics and user behavior.
In online social media platforms, users can express their ideas by posting original content or by adding comments and responses to existing posts, thus generating virtual discussions and conversations. Studying these conversations is essential for understanding the online communication behavior of users. This study proposes a novel approach to retrieve popular patterns on online conversations using network-based analysis. The analysis consists of two main stages: intent analysis and network generation. Users’ intention is detected using keyword-based categorization of posts and comments, integrated with classification through Naïve Bayes and Support Vector Machine algorithms for uncategorized comments. A continuous human-in-the-loop approach further improves the keyword-based classification. To build and understand communication patterns among the users, we build conversation graphs starting from the hierarchical structure of posts and comments, using a directed multigraph network. The experiments categorize 90% comments with 98% accuracy on a real social media dataset. The model then identifies relevant patterns in terms of shape and content; and finally determines the relevance and frequency of the patterns. Results show that the most popular online discussion patterns obtained from conversation graphs resemble real-life interactions and communication.
Design of Automated Sentiment or Opinion Discovery System to Enhance Its Perf...idescitation
In today’s social networking era, if one has to make
decision about any product, service or individual performance,
the availability of various comments, suggestions, ratings,
and feedbacks are abundant. The required decision support
data can be collected through different sources of Medias like
newspapers, blogs, and discussion forums and from internet
too. So surely, it leads to the selection of best product, service
or individual if it is analyzed efficiently. In leading and
competitive world, this is huge and practical need of industries,
organizations to empower their qualities. In the recent years,
the significant study is done in the field of sentiment analysis.
However, the earlier work focused the implementation and
evaluation of individual sub technique of sentiment analysis.
Though these implementations produces significant results
of sentiment or opinion analysis, the trust of decision makers
is still in dangling to accept the results of such analysis. In
this paper, initially, we have been described the brief review
about the sentiment or opinion analysis system. Then the
details are provided about the design and about how to build
an automated opinion discovery system to enhance
performance of sentiment or opinion analysis based on feature
extraction sentiment analysis sub technique, natural language
processing and data mining techniques in an integrated way
AN INTEGRATED RANKING ALGORITHM FOR EFFICIENT INFORMATION COMPUTING IN SOCIAL...ijwscjournal
Social networks have ensured the expanding disproportion between the face of WWW stored traditionally in search engine repositories and the actual ever changing face of Web. Exponential growth of web users and the ease with which they can upload contents on web highlights the need of content controls on material published on the web. As definition of search is changing, socially-enhanced interactive search methodologies are the need of the hour. Ranking is pivotal for efficient web search as the search performance mainly depends upon the ranking results. In this paper new integrated ranking model based on fused rank of web object based on popularity factor earned over only valid interlinks from multiple social forums is proposed. This model identifies relationships between web objects in separate social networks based on the object inheritance graph. Experimental study indicates the effectiveness of proposed Fusion based ranking algorithm in terms of better search results.
Identifying the Factors Affecting Users’ Adoption of Social NetworkingWaqas Tariq
Through the rapid expansion of information and communication technologies, social networking sites have received much more attention in the scope of internet communication. Success of a social web primarily depends on users’ satisfaction. In this context, this study aims to identify the influencing factors that affect users’ satisfaction towards social networking site use. A multidimensional model has been proposed based on the Information Quality, System Quality, Environmental and Affective dimensions to assess the effects of key variables – Semantic Intention, Usability, Web-Page Aesthetics, Subjective Norm and Trust- on users’ satisfaction. Facebook was chosen as a focused social networking site, because of its popularity. A comprehensive survey instrument was applied to 203 Facebook users. Also, Structural Equation Modeling, particularly Partial Least Square, was conducted to analyze the proposed research model. As a result, proposed multidimensional research model predicts the factors influencing users’ satisfaction towards social networking site use and relationships among these factors. The findings of this research will be valuable for literature by analyzing the influencing factors that have not been previously researched in the context of social networking satisfaction area.
Expectations for Electronic Debate Platforms as a Function of Application DomainIJERA Editor
Electronic debate (or commenting) platforms are used with many types of online applications, as a way to
engage the users or to provide enhancements, e.g., based on some type of collaborative filtering [1], [2]. The
applications enhanced with such debate platforms range widely : news, products, sport, religion, politics, etc.
Therefore, the emerging question is whether it is possible to make one electronic debate mechanism good for all
applications, and whether the studies on the success of a debate mechanism in one domain do automatically
apply to other application domains. Here we compare two traditional application domains of electronic debate
platforms: product evaluation and commented news. We exploit the fact that most users are very familiar with
both types of such applications, and therefore surveys can be designed to gauge reliably subtle differences
between expectations and properties of these domains. Based on over 1000 responses to surveys described here,
we are able to report statistically significant differences between the user behavior and expectations in the
studied domains.
Need Response 1The subcomponent of crowdsourcing ICT platform.docxvannagoforth
Need Response 1:
The subcomponent of crowdsourcing ICT platform technological architecture I would like to discuss is that gives additionally created an examination concerning public text information (for instance blog postings, comments, appraisals, etc.) and setting up this information sources using sentiment mining tools. The Web has changed the way wherein people express their emotions, offering them the capacity to post comments and reviews on business things and express their points of view on a a huge amount of issues in parties, talk get-togethers, visit rooms, long-broaden agreeable correspondence get-togethers and web diaries. This customer passed on the substance has been seen as a tremendous wellspring of business and political information. Notwithstanding, the tremendous the degree of this information and its normal language structure makes it difficult to remove the consistent areas, for instance, the general inclination/assessment (for instance positive, negative or sensible) on the particular subject (for instance a thing/affiliation or another methodology proposition) and the specific issues raised about it by the customers/visitors of these objectives. It is hidden motivation has been to enable firms to research online overviews and comments entered by customers of their things in various review districts, web diaries, social affairs, etc., in order to arrive at general judgments as for whether customers adored the thing or not (supposition assessment), and moreover continuously express finishes concerning features (traits) of the thing that has been commented on insistently or conflictingly (features extraction and examination).
This subcomponent performs three tasks, firstly it classifies the opinion text, a document which includes various declarations like a dialogue or a blog spot conveying a positive, negative or unprejudiced end. This is suggested as the record level evaluation examination. Secondly further focusing on sentence-level which deals with the gathering of a sentence as objective or passionate, it organizes each sentence in such a structure, that atmosphere it is a unique or targets (demonstrating whether it can express the inclination or not). For each sentence that is a conceptual (infers conveying an inclination) further, the portrayal is done as imparting an appositive, negative or unprejudiced supposition. Lastly extracting the most commented features of the commented articles, and for each commented feature further classification of relevant opinion is executed as positive, negative or unprejudiced.
References
Janssen, M., Wimmer, M. A., & Deljoo, A. (Eds.). (2015). Policy practice and digital science: Integrating complex systems, social simulation and public administration in policy research (Vol. 10). Springer
Need response 2:
nformation and communication technology platform has an important role to play in active crowdsourcing. A policy maker of a government agency initiates ...
How could a product or service is reasonably evaluated by anyone in the shortest time? A million dollar
question but it is having a simple answer: Sentiment analysis. Sentiment analysis is consumers review on
products and services which helps both the producers and consumers (stakeholders) to take effective and
efficient decision within a shortest period of time. Producers can have better knowledge of their products
and services through the sentiment analysis (ex. positive and negative comments or consumers likes and
dislikes) which will help them to know their products status (ex. product limitations or market status).
Consumers can have better knowledge of their interested products and services through the sentiment
analysis (ex. positive and negative comments or consumers likes and dislikes) which will help them to know
their deserving products status (ex. product limitations or market status). For more specification of the
sentiment values, fuzzy logic could be introduced. Therefore, sentiment analysis with the help of fuzzy logic
(deals with reasoning and gives closer views to the exact sentiment values) will help the producers or
consumers or any interested person for taking the effective decision according to their product or service
interest.
International Journal of Computer Science, Engineering and Information Techno...ijcseit
How could a product or service is reasonably evaluated by anyone in the shortest time? A million dollar
question but it is having a simple answer: Sentiment analysis. Sentiment analysis is consumers review on
products and services which helps both the producers and consumers (stakeholders) to take effective and
efficient decision within a shortest period of time. Producers can have better knowledge of their products
and services through the sentiment analysis (ex. positive and negative comments or consumers likes and
dislikes) which will help them to know their products status (ex. product limitations or market status).
Consumers can have better knowledge of their interested products and services through the sentiment
analysis (ex. positive and negative comments or consumers likes and dislikes) which will help them to know
their deserving products status (ex. product limitations or market status). For more specification of the
sentiment values, fuzzy logic could be introduced. Therefore, sentiment analysis with the help of fuzzy logic
(deals with reasoning and gives closer views to the exact sentiment values) will help the producers or
consumers or any interested person for taking the effective decision according to their product or service
interest.
How could a product or service is reasonably evaluated by anyone in the shortest time? A million dollar
question but it is having a simple answer: Sentiment analysis. Sentiment analysis is consumers review on
products and services which helps both the producers and consumers (stakeholders) to take effective and
efficient decision within a shortest period of time. Producers can have better knowledge of their products
and services through the sentiment analysis (ex. positive and negative comments or consumers likes and
dislikes) which will help them to know their products status (ex. product limitations or market status).
Consumers can have better knowledge of their interested products and services through the sentiment
analysis (ex. positive and negative comments or consumers likes and dislikes) which will help them to know
their deserving products status (ex. product limitations or market status). For more specification of the
sentiment values, fuzzy logic could be introduced. Therefore, sentiment analysis with the help of fuzzy logic
(deals with reasoning and gives closer views to the exact sentiment values) will help the producers or
consumers or any interested person for taking the effective decision according to their product or service
interest.
In this paper, a conceptual framework is proposed, supported in
the literature review, derived by identifying the main concepts
related to crowdsourcing, as well as ways of improving group
participation. We also propose a software solution that may be
used to support the crowdsourcing process. This software solution is inspired by the conceptual framework.
AN EXTENDED HYBRID RECOMMENDER SYSTEM BASED ON ASSOCIATION RULES MINING IN DI...cscpconf
Social groups in the form of different discussion forums are proliferating rapidly. Most of these forums have been created to exchange and share members’ knowledge in various domains.
Members in these groups may need to use and retrieve other members’ knowledge. Therefore, recommender systems are one of the techniques which can be employed in order to extract
knowledge based on the members needs and favorites. It is noteworthy that not only the users comments and posts can have valuable information, but also there are some other valuable information which can be obtained from social data; moreover, it could be extracted from relations and interactions among users. Hence, association rules mining techniques are one of the techniques which can be applied in order to extract more implicit data as input to the recommender system. Our objective in this study is to improve the performance of a hybrid
recommender system by defining new hybrid rules. In this regard, for the first time, we have defined new hybrid rules by considering both users and posts’ content data. Each of the defined rules has been examined on an asynchronous discussion group in this study. In addition, the impact of the defined rules on the precision and recall values of the recommender system has been examined. We found that according to this impact, a classification of the defined rules can
be considered and a number of weights can be assigned to each rule based on their impact and usability in the specific domain or application. It is noteworthy that the results of the
experiments have been promising
AN EXTENDED HYBRID RECOMMENDER SYSTEM BASED ON ASSOCIATION RULES MINING IN DI...csandit
Social groups in the form of different discussion forums are proliferating rapidly. Most of these
forums have been created to exchange and share members’ knowledge in various domains.
Members in these groups may need to use and retrieve other members’ knowledge. Therefore,
recommender systems are one of the techniques which can be employed in order to extract
knowledge based on the members’ needs and favorites. It is noteworthy that not only the users’
comments and posts can have valuable information, but also there are some other valuable
information which can be obtained from social data; moreover, it could be extracted from
relations and interactions among users. Hence, association rules mining techniques are one of
the techniques which can be applied in order to extract more implicit data as input to the
recommender system. Our objective in this study is to improve the performance of a hybrid
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Evaluation the Impact of Human Interaction/Debate on Online News to Improve User Interfaces for Debate Applications
1. Abdulrahman Alqahtani Int. Journal of Engineering Research and Applications www.ijera.com
ISSN: 2248-9622, Vol. 6, Issue 1, (Part - 3) January 2016, pp.45-55
www.ijera.com 45|P a g e
Evaluation the Impact of Human Interaction/Debate on Online
News to Improve User Interfaces for Debate Applications
Abdulrahman Alqahtani1,2
, Marius Silaghi2
(1Department of Computer Science, Najran University, Najran, Saudi Arabia)
(2Department of Computer Science, Florida Institute of Technology, Melbourne, FL, USA)
ABSTRACT
The average of many people trust online comments for any news as much as personal recommendations [1], [2].
In this paper, we analyzed the impact of the online news’s comments to evaluating the threading models of
electronic debates by using online surveys. In this paper, based on the results of our online survey of 500
participants, we evaluated whether forums with comments concerning online news are appropriate for the study
of debates. In particular, we have to verify whether the nature of discussions around news is argumentative and
whether the participating people expect to engage in multiple rounds of arguments. We presented
DirectDemocracyP2P application as a user interface for decentralized debates. In this paper, we evaluated and
analyzed the comments that were collected from online surveys to improve the DirectDemocracyP2P
applications. Also we have to verify whether the actual comments commonly submitted around news do go
beyond the simple advertisement of one own’s merchandise and attacks of competitors, into fair reviews of
news features and quality.
Keywords–User interfaces for Online News, Evaluation of the Impact of Threading Models on Online News,
Methodology, and Results
I. INTRODUCTION
Some of people who read the online news would
like to read and/or write comment on the article that
has been read. We live in a society where almost
everyone uses social media applications on devices
such as smart phones or tablets. These applications
include Facebook, Twitter, YouTube, Gmail, Google
Plus, Yahoo messenger, WhatsApp etc. [3], [4]. Most
of the recent studies focus on the impact of online
comments on open news [5]. This paper focuses on
analyzing and comparing threading models for
representing knowledge stemming from debates.
Peer to Peer starts systems for distributing, editing,
and contorting the online news items [5]. Direct
DemocracyP2P (DDP2P) provides a system, with
multiple graphical interfaces, for news that related to
motion in a given organization [6]. In this paper, we
present DDP2P application for debate threading.
Online networks, including Facebook and MySpace,
provide an easy way to create circles of friends.
These applications enable the people to connect with
the worldwide community. However,
they have not yet been studied from the perspective
of how they improve group decision making [1], [2].
Large amounts of data and spam that can occur in
decentralized social networks raise a challenge for
debate user interfaces. The problem that emerges is
to scientifically decide whether the debate user
interface mechanisms proposed in debate systems do
really offer the enhancements for which they were
proposed.
II. Background
Recently, we can describe the evolution of a
news as open news or open publishing e.g. Bruns.
Open news platforms can used in many interest fields
and topic from politics to entertainment e.g. Slashdot
[5].
Defining the Debate: In certain decision making
fora (such as parliaments, or electronically in
DirectDemocracyP2P), a debate focuses on a clear
motion (i.e., proposal of a decision) that is relevant to
a given organization. Users can vote on it with
justifications.
We differentiate between debates and
brainstorming sessions, namely where a question and
its possible answers were not yet crystallized. The
regular discussions commonly available with blogs
and electronic news are classified as brainstorming
sessions, while discussions associated with common
polls, news reviews and petition drives platforms are
classified as debates.
III. User Interfaces for Online News
The output of debates consists not only in the
decision to be done, but also in a better
understanding of the issue by the involved
participants. Besides improving their under- standing
of the discussed matter, involved participants can
also improve their understanding of each other’s
point of view. The obtained classification of the
goals of a debate is as follows:
RESEARCH ARTICLE OPEN ACCESS
2. Abdulrahman Alqahtani Int. Journal of Engineering Research and Applications www.ijera.com
ISSN: 2248-9622, Vol. 6, Issue 1, (Part - 3) January 2016, pp.45-55
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a) making a decision (count supports vs count
oppositions)
b) improving the understanding
– understanding the abstract matter
– understanding the participants’ point of view
The goal of our research is to identify ways of
measuring how well a debate platform helps in
achieving the goals mentioned at point (b), namely to
improve understanding. Understanding is improved
as the user gets acquaintance with the relevant
justification provided by other participants. An
essential ingredient comes from the correct
evaluation of the importance of a justification as
yielded by the number of participants supporting it.
Figure 1 User Interfaces for DirectDemocracyP2P
Android application
Another important factor in catalyzing the
understanding of a justification is the intensity with
which each participant supports that justification. In
electronic debates, users can support somebody
else’s justification as an alternative to providing
his/her own justification. Justifications with large
support can be favored by viewers, as they may
better represent the opinion of the group. A further
mechanism to help users locate relevant justifications
is based on threading. Namely, new justifications can
point to old justifications that they claim to refute or
enhance. Thereby people visualizing old
justifications are notified of the presence of the
refutation and enhancement claims. In a DDP2P
application, all debates and arguments with news
have to be related to a motion in a given
organization. The user can vote on any with only one
justification and he/she can post news linked to
motions or justifications. Here we introduce an
Android application for DDP2P according to motions
and justifications that are in the exit organization.
a) Motions: A motion is a proposal related to a
statute, constitutional amendment, or discussion
issue that is raised for the vote of a committee or
constituency. In some organizations (e.g., US towns),
the motions can be submitted to the town council1
only by certain members of the council. In other
organizations (e.g., Swiss towns) a motion can be
submitted by any group of citizens that gathers
signatures [6].
The mechanism of disseminating motions can be
used to help the community converge towards
enhanced versions of a motion. Discovery of better
versions of a motion can be boosted by an
appropriate threading mechanism, with each new
motion referring back to previous motions on which
it claims to improve. These references create a thread
that can be traversed by a user, or can be used by
automatic reasoning tools helping users in locating
promising motions.
b) Justifications: One of the benefits of gathering
votes for a motion is that constituents can get an
understanding concerning the positions of their
peers, and therefore better grasp the implications of a
given motion on their organization and on peer
members.
Namely, if a majority of peer members disagree
with a motion that the user has earlier believed to be
good, he may reconsider his position on the motion.
The peers could have potentially discovered
problems with that motion, problems communicated
via justifications that can make the constituent
withdraw his/her support. Withdrawing support for
an unpopular motion will save the time of the other
constituents who will be less tempted to spend time
reading it, and this will help the organization to save
the resources needed to move on the proposal and
organize an official ballot [6], [7]. Common
alternatives when voting on a motion are Sup- port,
Oppose, and Abstain. However, each submitted
motion can be customized to allow for any set of
possible reactions as appreciated by the author of the
motion. Poor choices are supposed to be correctable
by enhancements. As previously explained, the
understanding of the opinion of one’s peers can be
further improved by enabling the submitter of votes
3. Abdulrahman Alqahtani Int. Journal of Engineering Research and Applications www.ijera.com
ISSN: 2248-9622, Vol. 6, Issue 1, (Part - 3) January 2016, pp.45-55
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Figure 2 User Interfaces for DirectDemocracyP2P
Android application2
to associate a justification of their support or
opposition to the motion. Threading and thumbs
(technical term that everyone knows) in fora are used
for training an automatic moderator [7], [8].
c) Problem: The problem that emerges is to
scientifically quantify how some debate mechanism
supports decision making [7], [9], [10].
IV. METHODOLOGY
There are several types of debates, function of
the ad- dressed topic:
• Online Products: Online products sellers asking
customers to leave a review/comment on their
site exist.
• Online News: Readers of the online news
posting comments on a news article.
• Religion: People sharing information about their
religious beliefs.
• Science: People raising concerns related to the
significance and correctness of scientific issues.
• Politics: People sharing information about their
political beliefs.
• Sports: Comments and arguments around news
concerning sports.
V. Evaluation of the Impact of
Threading Models on Online News
We use surveys to extract the properties of each
type of debates, and to see the differences in their
rules as expected and deemed appropriate by users.
We started an online study from August to
September 2015 in which we presented a survey to
participants and asked them to answer its questions
using the Survey Monkey platform. In our study we
use the technique of submitting the questions in an
online survey to collect the data from online users.
We designed and distributed questionnaires in our
survey in a couple of languages (English and
Arabic). B. Study Questions Study questions
contained three groups:
• Participation Agreement: The first question in
our survey is a participation agreement.
Participation is voluntary.
• General Information: We collected general
information like gender, age range, secondary
language, and level of education to evaluate our
survey population.
• Understanding Questions: Participants
answered a chain of multiple choice questions to
determine the factors that attract the users while
reading or taping reviews (comments/threads)
for any online news.
C. Goals of Our Survey
The purpose of our surveys is to:
• Evaluate how comments for online news, differ
from other debates.
• Gather suggestion of how to improve user
interfaces for debate applications.
VI. RESULTS AND DISCUSSION
A. Participation Agreement (Institutional Review
Board (IRB) )
The first question in our survey asked the user to
accept a participation agreement.
We asked: Do you agree to the above terms? By
clicking Yes, you consent that you are willing to
answer the questions in this survey.
Key Finding:
99 percent accepted to answer our survey.
1 percent rejected to participate in our survey.
Analysis: Most of the participants accepted to
answer the questions in our survey (497 of 502) as
shown in Figure 3. This was an easy question
because this question confirmed the participation in
our survey.
Figure 3Institutional Review Board (IRB)
4. Abdulrahman Alqahtani Int. Journal of Engineering Research and Applications www.ijera.com
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B. General Information:
There were four questions about general
information. Every question had to fulfill the purpose
of the study.
1) Gender: This question aimed to know who was
more active in the debate, men or women. This
question will help to structure debate user interfaces
(DDP2P applications) according to the interaction of
humans.
We asked: What is your gender?
Figure 4Gender percent of participants in our
survey
Key Finding:
81.3 percent of participants were male.
18.7 percent of participants were female.
Analysis: Bother gender were willing to debate in
online news, according to this survey. This question
will lead to focusing on their interesting more, by
using ads, news, topics, etc., in a debate user
interface (DDP2P applications), in order to attract
them into successful debates.
2) Age Range: the age range question targeted the
age range of participants who are willing to debate.
We asked: What is your age range?
Key Finding:
4.8 percent of participants were less than 20.
46.3 percent of participants were between 20 and 30.
48.9 percent of participants were over than 30.
Figure 5Age Range of participants in our survey
Analysis: The greatest age range of participants, who
were willing to debate in this study, was older than
30 (465 of 924), then between 20 and 30 (225 of
460) as shown in Figure 5. This question gave us the
age range of participants whom we should focus on
when we improve the user interface of DDP2P
applications.
3) Secondary Language: The secondary language
question aimed to discover which languages are the
most popular in the debate.
We asked: What is your secondary language, if any?
Key Finding:
80.4 percent of participants whose second language
was English.
0.9 percent of participants whose second language
was Chinese.
0.4 percent of participants whose second language
was French.
2.0 percent of participants whose second language
was Spanish.
75.0 percent of participants whose second language
was Other.
Analysis: We found English was the most popular
language in our study (370 of 460) as shown in
Figure 6. From this question, in DDP2P applications,
we will suggest using English as a formal language
to communicate between users. Also, we will put
English as the default user interface for DDP2P
applications.
5. Abdulrahman Alqahtani Int. Journal of Engineering Research and Applications www.ijera.com
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Figure 6Secondary Language of participants in
our survey
4) Level of the Education: The level of education
question referred to the impact of level of education
on the debate.
We asked: What is your education level?
Key Finding:
15.2 percent of participants have a High School
degree
48.3 percent of participants have a Bachelor’s degree
26.7 percent of participants have a Master’s degree
9.8 percent of participants have a Ph.D degree
Analysis: Most participants have a Bachelor’s
degree (222 of 460) as shown in Figure 7. This
question showed us that most participants could be
familiar with any updates or developments for
improving the user interface of DDP2P applications
because the majority of participants had a Bachelor’s
degree.
Figure 7Level of Education of participants in our
survey
C. Survey Validity
We had a question to test the validity of our online
survey. The validity question depended on asking
questions which measured what we were supposed to
be measuring.
We asked: How likely would you be to read the
comments/threads of a news article after read article
online?
Key Finding:
19.8 percent of participants usually read the
comments/threads of a news article after read article
online.
73.5 percent of participants sometimes read the
comments/threads of a news article after read article
online.
6.7 percent of participants neverread the
comments/threads of a news article after read article
online.
Analysis: The result of this question referred to
whether the majority of participants would read a
news comments "Usually" (91 of 460) or
"Sometimes" (338 of 460) as shown in Figure 8.
Whoever answered "Never" for this question could
not continue to the next series of questions because
the remaining questions focused on actual readers of
news comments.
Figure 8The Validity of our Survey
D. Threads Questions:
We have several questions which focused on
comments of online news. Our samples were the
participants who read comments. They were
supposed to answer a chain of multiple choice
questions to determine the factors that attract users
while reading or taping comments/threads for any
online news. The results of those questions will help
us to improve our DirectDemocracyP2P applications.
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1) Trusting the Justifications:
Forty-three percent of participants were trusted to
read a brief comment (388 of 720) as shown in
Figure 9.
We asked: When you read comments on ant online
news, what types of comments/threads do you trust
the most?
Key Finding:
43.5 percent of participants were trusted to read a
brief comment.
22.3 percent of participants were trusted to read a
long comment.
34.2 percent of participants were not likely to trust
any online comments.
Figure 9: Trusting the Justifications
Analysis: Designing the brief comments by Limiting
the length of the motion will help to attract users to
debate according to the results of this question.
Limitation of the length of the debate arguments will
directly affect users’ acquisition and, in turn, trusting
the justifications about any given motion in the
DDP2P applications.
2) Sorting the Important Justification:
Most users would read up to 10 reviews according to
the results of this question (298 of 395) as shown in
Figure 10.
Figure 10: Sorting the Important Justification
We asked: How many comments do you normally
read in association with an online article, in case you
start reading its comments?
Key Finding:
32.4 percent of participants read 5 or less normally
read in association with an online article, in case you
start reading its comments.
43.0 percent of participants read 10 or less normally
read in association with an online article, in case you
start reading its comments.
24.8 percent of participants read more than 10
normally read in association with an online article, in
case you start reading its comments.
Analysis: In DDP2P applications, sorting the
important justifications among the top ten
justifications (around a given motion) will give the
user opportunity to read them.
3) Separating the Justification:
Sixty-nine percent of participants were likely to read
any type of the arguments (Positive or Negative
comments) for any debate (274 of 395) as shown in
Figure 11.
We asked: When you read comments for some
online news article, do you focus on comments that
Key Finding:
9.6 percent of participants were likely to read the
comments that are agreed with the article.
10.4 percent of participants were likely to read the
comments that are disagreed with the article.
6.3 percent of participants were likely to read the
comments that are agreed with the user’s opinion.
69.4 percent of participants were likely to read the
comments that are disagreed with the user’s opinion.
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Figure 11: Separating the Justification
Analysis: In DDP2P applications, we have already
separated the justification on a motion whether
Support, Oppose, or Abstain.
4) Showing the number of Justifications and
Witnesses:
Fifty-nine percent of participants disagreed with
the statement, "Would a number of positive
comments, the number of readers, or other rating
criteria, be enough for you to trust a specific news
from an online news?" (233 of 395) as shown in
Figure 12.
We asked: Are a number of positive comments, the
number of readers, or other rating criteria, enough for
you to trust a specific news from an online news?
Key Finding:
20.8 percent of participants answered (Yes).
20.3 percent of participants answered (Yes, if I do
not have personal opinion).
59.0 percent of participants answered (No).
Figure 12: Showing a number of positive reviews
(comments/threads) and the number of stars, or
other rating criteria
Analysis: Showing a number of positive comments,
the number of reader, or other rating criteria will
attract users to read and write comments and make
good arguments. In DDP2P, a number of
justifications, the number of witnesses, or other
rating criteria should be shown in the first page of the
user interface for the motion.
4) Form for Attention-Grabbing-Words:
Sixty-two per- cent of participants would be attracted
by any type of online news comments (Positive or
Negative Words)(248 of 395) as shown in Figure 13.
We asked: What types of words attract you the most
while reading comments for any online news?
Key Finding:
29.4 percent of participants were attracted by
positive words of arguments.
7.8 percent of participants were attracted by negative
words of arguments.
62.8 percent of participants were attracted by both
sides of arguments (Positive or Negative words).
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Figure 13Types of words that attract users
Analysis: In DDP2P applications, we could design a
form for attention- grabbing-words which would
attract users to become more involved in the debate.
5) Form for emphasizing words:
Forty-six percent of participants would expand
words, when you type a comment in reviews as
shown in Figure 14.
We asked: When you type a comment in reviews
(com- ments/threads) for any online news, do you
expand some words for emphasis? For example
verrrrrrrrrrrry
Key Finding:
6.3 percent of participants were always likely to
expand some words for emphasis when they typed a
comment in online reviews.
39.7 percent of participants were sometimes likely to
expand some words for emphasis when they typed a
comment in online reviews.
53.9 percent of participants were never likely to
expand some words for emphasis when they typed a
comment in online reviews.
Figure 14 Expanding some words for emphasis
Analysis:
In DDP2P applications, we can design a form
for emphasizing words which will attract users to
become more involved in the debate.
6) Form for Translating Words of the User
Region:
Sixty- three percent of participants would use argot
language from their region (251 of 395) as shown in
Figure 15.
We asked: When you type a comment in a review
(comments/threads) for any online news, do you use
argot language from your region?
Key Finding:
11.9 percent of participants were always likely to use
argot language from their region.
51.6 percent of participants were sometimes likely to
use argot language from their region.
36.5 percent of participants were never likely to use
argot language from their region.
Figure 15: Using argot language from user region
9. Abdulrahman Alqahtani Int. Journal of Engineering Research and Applications www.ijera.com
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Analysis: In DDP2P applications, we should design
a form for translating words of the user’s region to
English, and give some space to clarify these words
(enhancement).
7) Form for Supporting Translation:
Fifty-five percent of participants were never likely to
use words from other languages (219 of 395) as
shown in Figure 16.
We asked: When you type a comment in a review
(comments/threads) for any online news, do you use
some words from other languages?
Key Finding:
3.8 percent of participants were always likely to use
words from other languages
40.8 percent of participants were sometimes likely to
use words from other languages
55.9 percent of participants were never likely to use
words from other languages
Figure 16: Using any word from other languages
Analysis: In DDP2P applications, we should design
a form for sup- porting translation of words of the
users’ languages, and give the users space to explain
these words (explanation).
8) Benefit of Study Threads:
Thirty-four percent of participants said that comment
about any online news are argumentative reviews
while thirty percent described online reviews as
positive reviews. The rest of participants considered
online reviews as negative reviews as shown in
Figure 17.
We asked: From your perspective, how would you
generally describe reviews (comments/threads) about
any online news?
Key Finding:
34.4 percent of participants described online reviews
as argumentative comments
30.4 percent of participants described online reviews
as positive comments
35.2 percent of participants described online reviews
as negative comments
Figure 17: Benefit of Study Reviews/Threads
Analysis: The results of this question gave us the
benefit of studying online reviews (comments/
threads). There are a lot of users who trust online
reviews, especially if they are serious and positive
reviews.
10) Structured/Unstructured Platform for
Threads:
Fifty- eight percent of participants were likely
to prefer platforms for reviews (comments/threads)
of the online news to be structured, which could be a
specific question that the user should answer or
comment on. Structured platforms helped extract a
conclusion of arguments around the news as shown
in Figure 18.
We asked: How do you prefer platforms for reviews
(comments/threads) associated with with online to be
structured platforms or unstructured platforms?
Key Finding:
58.2 percent of participants preferred reviews
(comments/threads) for online news to be structured
platforms
41.8 percent of participants preferred reviews
(comments/threads) for online news to be
unstructured platforms.
10. Abdulrahman Alqahtani Int. Journal of Engineering Research and Applications www.ijera.com
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Figure 18: Structured/Unstructured Platform for
Reviews/Threads
Analysis:
Forty-one percent of participants were likely to
prefer re- views (comments/threads) for online news
to be unstructured platforms. In DDP2P applications,
we should have those two types of platforms.
Unstructured platforms could be used for peers to
join or create any organizations/motions, and
structured platforms could be used for voting to post
only one justification for any given motion, and
whether they support it or are against it.
VII. ACKNOWLEDGMENT
We are sincerely grateful to Dr. Muzaffar
Shaikh, Dr. John Lavelle, Dr. Khalid Abuhasel for
their support and sharing their truthful and
illuminating view on a number of issues related to
the survey.
VIII. CONCLUSION
Here we have analyzed the impact of reviews
(threads) for online news based on an online survey.
We evaluated whether forums with comments
concerning online news are appropriate for the study
of debates on ideas. In particular we found that the
discussions around news is argumentative and people
expected to engage in multiple rounds of arguments.
Also, we have gathered the following suggestions
that may be used to improve user interfaces for
debate applications:
• People believe that they “trust brief comments
over long comments”. Most people believe that
they “do not read more than 10 comments”.
Most people believe that they “like to read both
opposing arguments of a debate”, (despite the
evidence suggesting that people end up reading
only the news channels sharing their opinions).
• Most people believe that they are “satisfied by
know- ing the position of others without caring
about their arguments”. Most people believe that
they “are not biased by key- words in their
attention”.
• Half of the people believe that they “want to
display their emotions in their comments”.
• Most people believe that they like to display
“elements of their identity in their comments”.
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