TY - JOUR
T1 - TOSI
T2 - A trust-oriented social influence evaluation method in contextual social networks
AU - Liu, Guanfeng
AU - Zhu, Feng
AU - Zheng, Kai
AU - Liu, An
AU - Li, Zhixu
AU - Zhao, Lei
AU - Zhou, Xiaofang
PY - 2016/10/19
Y1 - 2016/10/19
N2 - 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.
AB - 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.
KW - social influence
KW - social network
KW - trust
UR - http://www.scopus.com/inward/record.url?scp=84979662851&partnerID=8YFLogxK
U2 - 10.1016/j.neucom.2015.11.129
DO - 10.1016/j.neucom.2015.11.129
M3 - Article
AN - SCOPUS:84979662851
SN - 0925-2312
VL - 210
SP - 130
EP - 140
JO - Neurocomputing
JF - Neurocomputing
ER -