Title: A novel estimation model for user relationship intensity in social network

Authors: Huijian Xu; Wanqiong Tao; Feipeng Guo

Addresses: Information Technology Department, Zhejiang Institute of Economics and Trade, Hangzhou City, China ' School of Management and E-Business, Zhejiang Gongshang University, Hangzhou City, China ' Modern Business Research Centre, Zhejiang Gongshang University, Hangzhou City, China; Information Technology Department, Zhejiang Institute of Economics and Trade, Hangzhou City, China

Abstract: With the development of social networks, the relationship intensity of social network users has become an increasingly important topic. This paper proposes an approach based on Sina and Tencent microblogs, which can be used to calculate the relationship intensity among users. It has considered the various relationship intensities in seven different fields, such as working, shopping, traveling, sports, entertainment and so on. However, most of the existing approaches only focus on the direct relationship intensity between different users in one activity field. They haven't taken the indirect relationship intensity into consideration. Therefore, in this paper, we propose a general relationship intensity that consists of both direct and indirect relationship intensity in the same activity field, even if there is only the indirect relationship between users. We conduct the experiment on Sina and Tencent microblog data sets, using the users' profile and interaction activities information. The analysis results on real data set show that our approach achieves superior performance to the existing methods.

Keywords: social network; relationship intensity; direct relationship; indirect relationship.

DOI: 10.1504/IJWMC.2019.099871

International Journal of Wireless and Mobile Computing, 2019 Vol.16 No.3, pp.272 - 280

Received: 15 Aug 2018
Accepted: 12 Nov 2018
Published online: 24 May 2019 *

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