Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Web Structure, Dynamics and Page Quality
SPIRE 2002 Proceedings of the 9th International Symposium on String Processing and Information Retrieval
The link prediction problem for social networks
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
ACM SIGKDD Explorations Newsletter
Structure and evolution of blogspace
Communications of the ACM - The Blogosphere
Page quality: in search of an unbiased web ranking
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Graphs over time: densification laws, shrinking diameters and possible explanations
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
A probabilistic approach to spatiotemporal theme pattern mining on weblogs
Proceedings of the 15th international conference on World Wide Web
Temporal Analysis of the Wikigraph
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
The eigenrumor algorithm for calculating contributions in cyberspace communities
Trusting Agents for Trusting Electronic Societies
On the relationship between novelty and popularity of user-generated content
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
To better stand on the shoulder of giants
Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries
On the Relationship between Novelty and Popularity of User-Generated Content
ACM Transactions on Intelligent Systems and Technology (TIST)
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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We study the problem of predicting the popularity of items in a dynamic environment in which authors post continuously new items and provide feedback on existing items. This problem can be applied to predict popularity of blog posts, rank photographs in a photo-sharing system, or predict the citations of a scientific article using author information and monitoring the items of interest for a short period of time after their creation. As a case study, we show how to estimate the number of citations for an academic paper using information about past articles written by the same author(s) of the paper. If we use only the citation information over a short period of time, we obtain a predicted value that has a correlation of r = 0.57 with the actual value. This is our baseline prediction. Our best-performing system can improve that prediction by adding features extracted from the past publishing history of its authors, increasing the correlation between the actual and the predicted values to r = 0.81.