杭州电子科技大学图书馆书目检索系统

Online Public Access Catalogue

题名/责任者:

Trust in social media / Jiliang Tang and Huan Liu

出版发行项:

San Rafael, California : Morgan & Claypool, c2015

ISBN:

9781627054041 :

ISBN:

1627054049

载体形态项:

xiii, 115 pages : illustrations; 24cm.

丛编说明:

Synthesis lectures on information security, privacy, and trust, 1945-9750 ; # 13

丛编统一题名:

Synthesis digital library of engineering and computer science

丛编统一题名:

Synthesis lectures on information security, privacy and trust ; # 13.

个人责任者:

Tang, Jiliang, author

附加个人名称:

Liu, Huan, 1958- author

论题主题:

Social media-Moral and ethical aspects

中图法分类号:

C912.3

一般附注:

Part of: Synthesis digital library of engineering and computer science

书目附注:

Includes bibliographical references (pages 99-113)

内容附注:

1. Introduction -- 1.1 Definitions of trust -- 1.1.1 Trust in psychology -- 1.1.2 Trust in sociology -- 1.1.3 Trust in economics -- 1.1.4 Trust in management -- 1.1.5 An interdisciplinary view of trust definitions -- 1.1.6 Discussions -- 1.2 Examples of online trust systems -- 1.2.1 E-commerce sites -- 1.2.2 Expert sites -- 1.2.3 Review sites -- 1.2.4 News sites -- 1.3 Computational tasks for trust -- 1.3.1 Representing trust -- 1.3.2 Predicting trust -- 1.3.3 Applying trust -- 1.3.4 Incorporating distrust -- 1.4 Summary

内容附注:

2. Representing trust -- 2.1 Properties of trust -- 2.1.1 Transitivity -- 2.1.2 Asymmetry -- 2.1.3 Composability -- 2.1.4 Correlation with similarity -- 2.1.5 Context dependence -- 2.1.6 Dynamic -- 2.2 Trust representations -- 2.2.1 Probabilistic vs. gradual representations -- 2.2.2 Single-dimensional vs. multi-dimensional representations -- 2.3 Recent advances of trust representations -- 2.3.1 Dimension correlation -- 2.3.2 Temporal information -- 2.3.3 Trust, untrust, and distrust

内容附注:

3. Predicting trust -- 3.1 Basic concepts -- 3.1.1 Definition -- 3.1.2 Classifications of trust metrics -- 3.1.3 A unified classification of trust metrics -- 3.2 Algorithms of trust metrics -- 3.2.1 Global trust metrics -- 3.2.2 Local trust metricS -- 3.3 Evaluation of predicting trust -- 3.3.1 Datasets for predicting trust -- 3.3.2 Ranking-based evaluation -- 3.3.3 RMSE evaluation -- 3.3.4 Leave-one-out cross-validation evaluation -- 3.3.5 F-measure evaluation -- 3.4 Recent advances in predicting trust -- 3.4.1 Predicting multi-dimensional trust -- 3.4.2 Predicting trust with temporal dynamics -- 3.4.3 Predicting trust with social theories

内容附注:

4. Applying trust -- 4.1 Traditional recommender systems -- 4.1.1 Content-based recommender systems -- 4.1.2 Collaborative filtering-based recommender systems -- 4.1.3 Hybrid recommender systems -- 4.2 Trust-aware recommender systems -- 4.2.1 Problem statement -- 4.2.2 Opportunities from trust information -- 4.3 Existing trust-aware recommender systems -- 4.3.1 Memory-based trust-aware recommender systems -- 4.3.2 Model-based trust-aware recommender systems -- 4.4 Performance evaluation -- 4.4.1 Datasets -- 4.4.2 Evaluation metrics -- 4.5 Recent advances in trust-aware recommender systems -- 4.5.1 Global trust in recommendation -- 4.5.2 Multi-faceted trust in recommendation -- 4.5.3 Distrust in recommendation

内容附注:

5. Incorporating distrust -- 5.1 Incorporating distrust into trust representations -- 5.1.1 Understandings from social sciences -- 5.1.2 An computational understanding in social media -- 5.1.3 Distrust in trust representations -- 5.1.4 Social theories for trust/distrust networks -- 5.2 Incorporating distrust into predicting trust -- 5.2.1 Distrust in global trust metrics -- 5.2.2 Distrust in local trust metrics -- 5.3 Incorporating distrust into trust-aware recommender systems -- 5.3.1 Memory-based methods -- 5.3.2 Model-based methods -- 5.4 Recent advances in incorporating distrust -- 5.4.1 Sign prediction -- 5.4.2 Distrust prediction

内容附注:

6. Epilogue -- 6.1 Future directions in predicting trust -- 6.2 Future directions in applying trust -- 6.3 Future directions in incorporating distrust -- Bibliography -- Authors' biographies

摘要附注:

Social media greatly enables people to participate in online activities and shatters the barrier for online users to create and share information at any place at any time. However, the explosion of user-generated content poses novel challenges for online users to find relevant information, or, in other words, exacerbates the information overload problem. On the other hand, the quality of user-generated content can vary dramatically from excellence to abuse or spam, resulting in a problem of information credibility. The study and understanding of trust can lead to an effective approach to addressing both information overload and credibility problems. Trust refers to a relationship between a trustor (the subject that trusts a target entity) and a trustee (the entity that is trusted). In the context of social media, trust provides evidence about with whom we can trust to share information and from whom we can accept information without additional verification. With trust, we make the mental shortcut by directly seeking information from trustees or trusted entities, which serves a two-fold purpose: without being overwhelmed by excessive information (i.e., mitigated information overload) and with credible information due to the trust placed on the information provider (i.e., increased information credibility). Therefore, trust is crucial in helping social media users collect relevant and reliable information, and trust in social media is a research topic of increasing importance and of practical significance. This book takes a computational perspective to offer an overview of characteristics and elements of trust and illuminate a wide range of computational tasks of trust. It introduces basic concepts, deliberates challenges and opportunities, reviews state-of-the-art algorithms, and elaborates effective evaluation methods in the trust study. In particular, we illustrate properties and representation models of trust, elucidate trust prediction with representative algorithms, and demonstrate real-world applications where trust is explicitly used. As a new dimension of the trust study, we discuss the concept of distrust and its roles in trust computing

载体形态附注:

Also available online

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