Discovering social structures of local influence by using tweetStimuli

被引：2

作者：

Tejeda-Gomez, Arturo ^{[1
]}

Sanchez-Marre, Miquel ^{[1
]}

Pujol, Josep M. ^{[2
]}

机构：

[1] Univ Politecn Catalunya Barcelona Tech, Knowledge Engn & Machine Learning Grp, Barcelona 08034, Spain

[2] 3scale Networks SL, Barcelona 08013, Spain

来源：

INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS | 2014年 / 91卷 / 02期

关键词：

social networks; influence; social structures; clustering;

D O I：

10.1080/00207160.2013.849806

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Information diffusion in large-scale networks has been studied to identify the users influence. The influence has been targeted as a key feature either to reach large populations or influencing public opinion. Through the use of micro-blogs, such as Twitter, global influencers have been identified and ranked based on message propagation (retweets). In this paper, a new application is presented, which allows to find first and classify then the local influence on Twitter: who have influenced you and who have been influenced by you. Until now, social structures of tweets' original authors that have been either retweeted or marked as favourites are unobservable. Throughout this application, these structures can be discovered and they reveal the existence of communities formed by users of similar profile (that are connected among them) interrelated with other similar profile users' communities.

引用

页码：291 / 303

页数：13

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