The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Mining the network value of customers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
The dynamics of viral marketing
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Identifying the influential bloggers in a community
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Twitter power: Tweets as electronic word of mouth
Journal of the American Society for Information Science and Technology
Learning influence probabilities in social networks
Proceedings of the third ACM international conference on Web search and data mining
TwitterRank: finding topic-sensitive influential twitterers
Proceedings of the third ACM international conference on Web search and data mining
Outtweeting the twitterers - predicting information cascades in microblogs
WOSN'10 Proceedings of the 3rd conference on Online social networks
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
Finding trendsetters in information networks
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
LBSNRank: personalized pagerank on location-based social networks
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Predicting responses to microblog posts
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Using link analysis to discover interesting messages spread across Twitter
TextGraphs-7 '12 Workshop Proceedings of TextGraphs-7 on Graph-based Methods for Natural Language Processing
Journal of the American Society for Information Science and Technology
Information-theoretic measures of influence based on content dynamics
Proceedings of the sixth ACM international conference on Web search and data mining
Retweet or not?: personalized tweet re-ranking
Proceedings of the sixth ACM international conference on Web search and data mining
SocialTrends: a web application for monitoring and visualizing users in social media
SocInfo'12 Proceedings of the 4th international conference on Social Informatics
Determining credibility from social network structure
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Application of AVS-P10 mobile speech and audio coding in social multimedia
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
ProfileRank: finding relevant content and influential users based on information diffusion
Proceedings of the 7th Workshop on Social Network Mining and Analysis
Information diffusion in online social networks: a survey
ACM SIGMOD Record
Topical authority propagation on microblogs
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
Proceedings of the 19th international conference on Intelligent User Interfaces
Aligning principal and agent's incentives: A principal-agent perspective of social networking sites
Expert Systems with Applications: An International Journal
Identifying interesting Twitter contents using topical analysis
Expert Systems with Applications: An International Journal
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The ever-increasing amount of information flowing through Social Media forces the members of these networks to compete for attention and influence by relying on other people to spread their message. A large study of information propagation within Twitter reveals that the majority of users act as passive information consumers and do not forward the content to the network. Therefore, in order for individuals to become influential they must not only obtain attention and thus be popular, but also overcome user passivity. We propose an algorithm that determines the influence and passivity of users based on their information forwarding activity. An evaluation performed with a 2.5 million user dataset shows that our influence measure is a good predictor of URL clicks, outperforming several other measures that do not explicitly take user passivity into account. We demonstrate that high popularity does not necessarily imply high influence and vice-versa.