JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2016, Vol. 51 ›› Issue (9): 113-120.doi: 10.6040/j.issn.1671-9352.2.2015.228

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EIP: discovering influential bloggers by user similarity and topic timeliness

ZHU Sheng, ZHOU Bin, ZHU Xiang   

  1. School of Computer, National University of Defense Technology, Changsha 410073, Hunan, China
  • Received:2015-10-12 Online:2016-09-20 Published:2016-09-23

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Abstract: Enormous information flowing through Online Social Media nowadays, spreading through hundreds of millions of users with different influence in the network. EIP(extended influence-passivity), an extension of IP(influence passivity)algorithm, is proposed to identify influencers in social network based on users forwarding activity. EIP measures the influence and passivity of users taking both pair wise topical similarity and timeliness feature of information into account. An evaluation performed with about 100 000 user dataset crawled from Sina micro-blog shows that EIP outperforms than other algorithms, including the original IP and TwitterRank.

Key words: social network, passivity, influential blogger identification, influential

CLC Number: 

  • TP393
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