OHSUMED: an interactive retrieval evaluation and new large test collection for research
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
The link prediction problem for social networks
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Application of kernels to link analysis
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Introduction to Information Retrieval
Introduction to Information Retrieval
Local Probabilistic Models for Link Prediction
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Learning spectral graph transformations for link prediction
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Social influence analysis in large-scale networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Walking in facebook: a case study of unbiased sampling of OSNs
INFOCOM'10 Proceedings of the 29th conference on Information communications
Scalable influence maximization for prevalent viral marketing in large-scale social networks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Understanding retweeting behaviors in social networks
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Everyone's an influencer: quantifying influence on twitter
Proceedings of the fourth ACM international conference on Web search and data mining
Inferring Networks of Diffusion and Influence
ACM Transactions on Knowledge Discovery from Data (TKDD)
Retweet Modeling Using Conditional Random Fields
ICDMW '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining Workshops
Co-factorization machines: modeling user interests and predicting individual decisions in Twitter
Proceedings of the sixth ACM international conference on Web search and data mining
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Microblogs such as Twitter support a rich variety of user interactions using hashtags, urls, retweets and mentions. Microblogs are an exemplar of a hybrid network; there is an explicit network of followers, as well as an implicit network of users who retweet other users, and users who mention other users. These networks are important proxies for influence. In this paper, we develop a comprehensive behavioral model of an individual user and her interactions in the hybrid network. We choose a focal user and predict those users who will be influenced by her, and will retweet and/or mention the focal user, in the near future. We define a potential function, based on a hybrid network, which reflects the likelihood of a candidate user being influenced by, and having a specific type of link to, a focal user, in the future. We show that the potential function based prediction model converges to the Bonacich centrality metric. We develop a fast unsupervised solution which approximates the future hybrid network and the future Bonacich potential. We perform an extensive evaluation over a microblog network and a stream of tweets from Twitter. Our solution outperforms several baseline methods including ones based on singular value decomposition (SVD) and a supervised Ranking SVM.