在社交媒体上鉴别有影响力的用户

更新于 2015年6月8日 问答
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0 2015年6月8日

Influential User Identification in Online Social Networks

contributors: @唐小sin @善良的右行

discussion: https://github.com/memect/hao/issues/89

keywords: 意见领袖 ( opinion leader), user influence, influential spreaders , influential user , twitter ,

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善良的右行:@好东西传送门 这几篇论文略旧……当然引用率是不用说的……貌似问题本质是重要节点挖掘……菜鸟冒泡一下……不知说的对不对…… (今天 14:45)

好东西传送门:发现重要节点一直是社交网络研究的重要问题, 研究热点大约在2007~2010社交媒体蓬勃发展的时候, 2014年已经有influential user identification的综述了.鉴于这类研究的算法并不困难,但数据量较大且较难获得,研究前沿已经逐渐从学术界转移到工业界/创业应用。http://t.cn/RPQfWRW (52分钟前)

唐小sin:的确是这样,现在social influence这块需要一个很好的问题去解,感觉就是做得太多很难入手。

唐小sin:任何influence的文章都可以哪来读读,而至于意见领袖不妨看看twitterrank (今天 15:13)

好东西传送门:回复@唐小sin: 这篇文章很不错哦, 还对比了TunkRank, Topic-sensitive PageRank (TSPR) (44分钟前)

善良的右行:@好东西传送门 惭愧,我也是菜鸟,当然很乐意共享:Identification of influentialspreaders in complex networks;Leaders in Social Networks, the Delicious Case; Absence of influential spreaders in rumor dynamics,都是牛人牛文……

@好东西传送门: 回复@善良的右行: 这几个推荐文章都很好呀,第一篇引用率都快400了. 要不是了解领域,谁能想到这个关键词呢, influential spreaders . 意共享:Identification of influentialspreaders in complex networks;Leaders in Social Networks, the De

readings

industry

http://mashable.com/2014/02/25/socialrank-brands/ SocialRank Tool Helps Brands Find Most Valuable Followers (2014)

http://www.smallbusinesssem.com/find-interesting-influential-twitter-users/3974/ Quick Way to Find Interesting & Influential Twitter Users (2011)

readings

influential user/spreader identification/ranking

http://link.springer.com/chapter/10.1007/978-3-319-01778-5_37 Survey of Influential User Identification Techniques in Online Social Networks (2014) Advances in Intelligent Systems and Computing

http://dl.acm.org/citation.cfm?id=1835935 Yu Wang, Gao Cong, Guojie Song, and Kunqing Xie. 2010. Community-based greedy algorithm for mining top-K influential nodes in mobile social networks. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD ’10)

http://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1503&context=sis_research Twitterrank: Finding Topic-Sensitive Influential Twitterers 2010 @唐小sin 推荐

http://www.anderson.ucla.edu/faculty/anand.bodapati/Determining-Influential-Users.pdf Determining Influential Users in Internet Social Networks

http://polymer.bu.edu/hes/articles/kghlmsm10.pdf Identification of influential spreaders in complex networks @善良的右行 推荐

http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0021202 Lü L, Zhang Y-C, Yeung CH, Zhou T (2011) Leaders in Social Networks, the Delicious Case. PLoS ONE 6(6) @善良的右行 推荐

http://arxiv.org/pdf/1112.2239.pdf Absence of influential spreaders in rumor dynamics @善良的右行 推荐

measure influence

http://blog.datalicious.com/awesome-new-research-measuring-twitter-user-influence-from-meeyoung-cha-max-planck-institute/ Awesome new research: Measuring twitter user influence from Meeyoung Cha, Max Planck Institute (2010) read the original paper below

http://www.aaai.org/ocs/index.php/ICWSM/ICWSM10/paper/viewFile/1538%20Amit%20Goyal%2C%20Francesco%20Bonchi%2C%20Laks%20V.%20S.%20Lakshmanan%3A%20Approximation%20Analysis%20of%20Influence%20Spread%20in%20Social%20Networks%20CoRR%20abs/1826 Measuring User Influence in Twitter: The Million Follower Fallacy

http://dl.acm.org/citation.cfm?id=2480726 Mario Cataldi, Nupur Mittal, and Marie-Aude Aufaure. 2013. Estimating domain-based user influence in social networks. In Proceedings of the 28th Annual ACM Symposium on Applied Computing (SAC ’13).

http://www.cse.ust.hk/~qnature/pdf/globecom13.pdf Analyzing the Influential People in Sina Weibo Dataset (2013)

http://dl.acm.org/citation.cfm?id=1935845 Eytan Bakshy, Jake M. Hofman, Winter A. Mason, and Duncan J. Watts. 2011. Everyone’s an influencer: quantifying influence on twitter. In Proceedings of the fourth ACM international conference on Web search and data mining (WSDM ’11)

related

http://en.wikipedia.org/wiki/Opinion_leadership

http://dl.acm.org/citation.cfm?id=2503797 Adrien Guille, Hakim Hacid, Cecile Favre, and Djamel A. Zighed. 2013. Information diffusion in online social networks: a survey. SIGMOD Rec. 42, 2 (July 2013), 17-28.

http://dl.acm.org/citation.cfm?id=2601412 Charu Aggarwal and Karthik Subbian. 2014. Evolutionary Network Analysis: A Survey. ACM Comput. Surv. 47, 1, Article 10 (May 2014), 36 pages.

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