Identifying Influential People Based on Interaction Strength

Muhammad Azam Zia, Zhongbao Zhang, Liutong Chen, Haseeb Ahmad and Sen Su
Volume: 13, No: 4, Page: 987 ~ 999, Year: 2017
10.3745/JIPS.04.0041
Keywords: Influence, Interaction, IPRank, Micro-Blog, Online Social Network
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Abstract
Extraction of influential people from their respective domains has attained the attention of scholastic community during current epoch. This study introduces an innovative interaction strength metric for retrieval of the most influential users in the online social network. The interactive strength is measured by three factors, namely re-tweet strength, commencing intensity and mentioning density. In this article, we design a novel algorithm called IPRank that considers the communications from perspectives of followers and followees in order to mine and rank the most influential people based on proposed interaction strength metric. We conducted extensive experiments to evaluate the strength and rank of each user in the micro-blog network. The comparative analysis validates that IPRank discovered high ranked people in terms of interaction strength. While the prior algorithm placed some low influenced people at high rank. The proposed model uncovers influential people due to inclusion of a novel interaction strength metric that improves results significantly in contrast with prior algorithm.

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Cite this article
IEEE Style
Muhammad Azam Zia, Zhongbao Zhang, Liutong Chen, Haseeb Ahmad and Sen Su, "Identifying Influential People Based on Interaction Strength," Journal of Information Processing Systems, vol. 13, no. 4, pp. 987~999, 2017. DOI: 10.3745/JIPS.04.0041.

ACM Style
Muhammad Azam Zia, Zhongbao Zhang, Liutong Chen, Haseeb Ahmad and Sen Su, "Identifying Influential People Based on Interaction Strength," Journal of Information Processing Systems, 13, 4, (2017), 987~999. DOI: 10.3745/JIPS.04.0041.