Journal
NEUROCOMPUTING
Volume 210, Issue -, Pages 130-140Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2015.11.129
Keywords
Social network; Social influence; Trust
Categories
Funding
- Natural Science Foundation of China [61303019, 61402312, 61402313, 61232006, 61003044, 61440053]
- Doctoral Fund of Ministry of Education of China [20133201120012]
- Postdoctoral Science Foundation of China [2015M571805]
- Collaborative Innovation Center of Novel Software Technology and Industrialization, Jiangsu, China
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Online Social Networks (OSNs) have been used as the means for a variety of applications. For example, social networking platform has been used in employment system, e-Commerce and CRM system to improve the quality of recommendations with the assistance of social networks. In these applications, social influence acts as a significant role, affecting people's decision-making. However, the existing social influence evaluation methods do not fully consider the social contexts, i.e., the social relationships and the social trust between participants, and the preferences of participants, which have significant impact on social influence evaluation in OSNs. Thus, these existing methods cannot deliver accurate social influence evaluation results. In our paper, we propose a Trust-Oriented Social Influence evaluation method, called TOSI, with taking the social contexts into account. We conduct experiments onto two real social network datasets, i.e., Epinions and DBLP. The experimental results illustrate that our TOSI method greatly outperforms the state-of-the-art method SoCap in terms of effectiveness, efficiency and robustness. (C) 2016 Elsevier B.V. All rights reserved.
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