SimRank: a measure of structural-context similarity
Proceedings of the eighth 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
A Parameterized Probabilistic Model of Network Evolution for Supervised Link Prediction
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
The link-prediction problem for social networks
Journal of the American Society for Information Science and Technology
Link Prediction of Social Networks Based on Weighted Proximity Measures
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Collaborative filtering with temporal dynamics
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Locality preserving nonnegative matrix factorization
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
TwitterRank: finding topic-sensitive influential twitterers
Proceedings of the third ACM international conference on Web search and data mining
Towards time-aware link prediction in evolving social networks
Proceedings of the 3rd Workshop on Social Network Mining and Analysis
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
LINKREC: a unified framework for link recommendation with user attributes and graph structure
Proceedings of the 19th international conference on World wide web
New perspectives and methods in link prediction
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A Unified Framework for Link Recommendation Using Random Walks
ASONAM '10 Proceedings of the 2010 International Conference on Advances in Social Networks Analysis and Mining
Structural Predictors of Tie Formation in Twitter: Transitivity and Mutuality
SOCIALCOM '10 Proceedings of the 2010 IEEE Second International Conference on Social Computing
Supervised random walks: predicting and recommending links in social networks
Proceedings of the fourth ACM international conference on Web search and data mining
Link formation analysis in microblogs
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Who will follow whom? exploiting semantics for link prediction in attention-information networks
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
LaFT-tree: perceiving the expansion trace of one's circle of friends in online social networks
Proceedings of the sixth ACM international conference on Web search and data mining
Predicting interactions in online social networks: an experiment in Second Life
Proceedings of the 4th International Workshop on Modeling Social Media
Learning latent friendship propagation networks with interest awareness for link prediction
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Link recommendation for promoting information diffusion in social networks
Proceedings of the 22nd international conference on World Wide Web companion
Structural-interaction link prediction in microblogs
Proceedings of the 22nd international conference on World Wide Web companion
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With hundreds of millions of participants, social media services have become commonplace. Unlike a traditional social network service, a microblogging network like Twitter is a hybrid network, combining aspects of both social networks and information networks. Understanding the structure of such hybrid networks and predicting new links are important for many tasks such as friend recommendation, community detection, and modeling network growth. We note that the link prediction problem in a hybrid network is different from previously studied networks. Unlike the information networks and traditional online social networks, the structures in a hybrid network are more complicated and informative. We compare most popular and recent methods and principles for link prediction and recommendation. Finally we propose a novel structure-based personalized link prediction model and compare its predictive performance against many fundamental and popular link prediction methods on real-world data from the Twitter microblogging network. Our experiments on both static and dynamic data sets show that our methods noticeably outperform the state-of-the-art.