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

Previous Articles     Next Articles

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

PDF (PC)

937

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
[1] ROMERO D, GALUBA W, ASUR S, et al.Influence and passivity in social media[J]. Ssrn Electronic Journal, 2010, 6913(1):18-33.
[2] KATZ E. The two-step flow of communication: An up-to-date report on an hypothesis[J]. Public Opinion Quarterly, 1957, 21(1):61-78.
[3] YOUNG H P. The diffusion of innovations in social networks[J]. General Information, 2000, 413(1): 2329-2334.
[4] KITSAK M, GALLOS L, HAVLIN S, et al. Identification of influential spreaders in complex networks[J]. Nature Physics, 2010, 6(11):888-893.
[5] CHA M, HADDADI H, BENEVENUTO F, et al. Measuring user influence in twitter: the million follower fallacy[C] //Proceedings of the 4th International AAAI Conference on Weblogs and Social Media(ICWSM 2010).[S.l.] :AAAI Press, 2010:10-17.
[6] CATALDI M, CARO L D, SCHIFANELLA C. Emerging topic detection on Twitter based on temporal and social terms evaluation[J]. Preceedings of 10th International Workshop on Multimedia Data Mining. NewYork: ACM, 2010:1-10.
[7] TUNKELANG D. A Twitter analogy to pagerank[EB/OL]. [2015-03-26].http: //thenoisychannel.com/2009/01/13/atwitter-analog-to-pagemark/.
[8] WENG J, LIM E P, JIANG J, et al. TwitterRank: finding topic-sensitive influential twitterers[J]. Proceedings of the 3rd ACM International Conference on Web Search and Data Mining-WSDM 2010.New Yok: ACM, 2010: 261-270.
[9] DING Z, JIA Y, ZHOU B, et al. Mining topical influencers based on the multi relational network in micro-blogging sites[J]. China Communications, 2013, 10(1): 93-104.
[10] KLEINBERG J. Authoritative sources in a hyperlinked environment[J]. Journal of the ACM, 1999, 46(5): 604-632.
[11] 丁兆云, 周斌, 贾焰, 等. 微博中基于多关系网络的话题层次影响力分析[J].计算机研究与发展, 2013, 10: 2155-2175. DING Zhaoyun, ZHOU Bin, JIA Yan, et al. Topic Influence analysis based on the multi-relational network in microblogs[J]. Journal of Computer Research and Development, 2013, 10:2155-2175.
[1] SUI Yun-xian, LIU Yong. Mining algorithm of E-burt structural hole based on two-step neighbor [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(9): 59-68.
[2] ZHANG Zhong-jun, ZHANG Wen-juan, YU Lai-hang, LI Run-chuan. A community division method based on network distance and content similarity in micro-blog social network [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(7): 97-103.
[3] DENG Xiao-fang, ZHONG Yuan-sheng, L(¨overU)Lin-yuan, WANG Ming-wen, XIONG Nai-xue. Mass diffusion on coupled social networks [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(3): 51-59.
[4] CAI Hong-yun, MA Xiao-xue. Access control based on relationship strength for online social network [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2016, 51(7): 90-97.
[5] ZHANG Shao-qun, WEI Jing-jing, LIAO Xiang-wen, JIAN Si-yuan, CHEN Guo-long. Emotional contagion in Twitter [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2016, 51(1): 71-76.
[6] LI Qi1,2, MA Jun1,2*. Person′s name disambiguation based on person  related social communities [J]. J4, 2012, 47(3): 33-37.
[7] WANG Fang, GUO Hua-Ping, NIU Chang-Yong, FAN Ming. New email community clustering method based on EVS similarity   [J]. J4, 2010, 45(3): 34-40.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright 2018 © Editorial office of JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE)
Supported by Beijing Magtech Co.Ltd