Proceedings ArticleDOI
Modelling Influence in a Social Network: Metrics and Evaluation
Behnam Hajian,Tony White +1 more
- pp 497-500
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TLDR
The hypothesis explored in this paper is that Influence Rank can be quantified based on the interaction between users and their behavior and results supporting the utility of the measure and the accuracy of its estimation using the Page Rank approximation are presented.Abstract:
Social recommender systems are a recently introduced type of decision support system. One of the issues to be resolved in social recommender systems is the identification of opinion leaders in a network. The focus of this paper is the analysis of a network based on the interactions between users called behavioral analysis. The hypothesis explored in this paper is that Influence Rank can be quantified based on the interaction between users and their behavior. The Influence Rank for a node is defined as the average Influence Rank of its neighborhoods combined with another index called Magnitude of Influence. The correlation between the proposed indices is analyzed in this paper. This combined measure is calculated by a recursive algorithm whose calculation complexity is non-polynomial. However, this measure can be estimated by using the Page Rank algorithm. Results supporting the utility of the measure and the accuracy of its estimation using the Page Rank approximation are presented.read more
Citations
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Journal ArticleDOI
Measuring user influence on Twitter
TL;DR: The purpose of this article is to collect and classify the different Twitter influence measures that exist so far in literature, which are very diverse and based on simple metrics provided by the Twitter API, while others are based on complex mathematical models.
Journal ArticleDOI
Influence analysis in social networks: A survey
TL;DR: This survey aims to pave a comprehensive and solid starting ground for interested readers by soliciting the latest work in social influence analysis from different levels, such as its definition, properties, architecture, applications, and diffusion models.
Proceedings ArticleDOI
Klout score: Measuring influence across multiple social networks
TL;DR: This work proposes a hierarchical framework for generating an influence score for each user, by incorporating information for the user from multiple networks and communities, and proves the correctness of the score by showing that users with higher scores are able to spread information more effectively in a network.
Journal ArticleDOI
Social context in sentiment analysis: Formal definition, overview of current trends and framework for comparison
TL;DR: This work aims to bridge the gap in analysis of sentiment analysis in social media by providing a formal definition of social context and a framework for classifying and comparing approaches that use social context; a review of existing works based on the defined framework.
Journal ArticleDOI
ISTS: Implicit social trust and sentiment based approach to recommender systems
Dimah Alahmadi,Xiao-Jun Zeng +1 more
TL;DR: A novel personalized Recommender System (RS) framework, so-called Implicit Social Trust and Sentiment (ISTS) based RS which draws user preferences by exploring the user’s Online Social Networks (OSNs) and utilizes the widely available information from such networks.
References
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Proceedings Article
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TL;DR: This paper describes PageRank, a mathod for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them, and shows how to efficiently compute PageRank for large numbers of pages.
Proceedings ArticleDOI
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Evaluating collaborative filtering recommender systems
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Journal ArticleDOI
A study of normative and informational social influences upon individual judgment.
Morton Deutsch,Harold B. Gerard +1 more
TL;DR: Several modifications of the Asch experiment in which the S judges the length of lines in the company of a group of “stooges” who carry out the experimenter's instructions are described.
Journal ArticleDOI
Network Analysis in the Social Sciences
TL;DR: The kinds of things that social scientists have tried to explain using social network analysis are reviewed and a nutshell description of the basic assumptions, goals, and explanatory mechanisms prevalent in the field is provided.