Mining knowledge-sharing sites for viral marketing
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
Personalized recommendation driven by information flow
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
The dynamics of viral marketing
ACM Transactions on the Web (TWEB)
Information flow modeling based on diffusion rate for prediction and ranking
Proceedings of the 16th international conference on World Wide Web
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Can social bookmarking enhance search in the web?
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Can social bookmarking improve web search?
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Influence and correlation in social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Feedback effects between similarity and social influence in online communities
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Personalized recommendation in social tagging systems using hierarchical clustering
Proceedings of the 2008 ACM conference on Recommender systems
Recommending scientific articles using citeulike
Proceedings of the 2008 ACM conference on Recommender systems
Signpost from the masses: learning effects in an exploratory social tag search browser
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A measurement-driven analysis of information propagation in the flickr social network
Proceedings of the 18th international conference on World wide web
Social influence analysis in large-scale networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Social recommender systems for web 2.0 folksonomies
Proceedings of the 20th ACM conference on Hypertext and hypermedia
Ballot box communication in online communities
Communications of the ACM - The Status of the P versus NP Problem
Social influence and the diffusion of user-created content
Proceedings of the 10th ACM conference on Electronic commerce
On social networks and collaborative recommendation
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Collaborative filtering for social tagging systems: an experiment with CiteULike
Proceedings of the third ACM conference on Recommender systems
A social recommendation framework based on multi-scale continuous conditional random fields
Proceedings of the 18th ACM conference on Information and knowledge management
Learning influence probabilities in social networks
Proceedings of the third ACM international conference on Web search and data mining
Patterns of influence in a recommendation network
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Modelling user behaviour and interactions: augmented cognition on the social web
FAC'11 Proceedings of the 6th international conference on Foundations of augmented cognition: directing the future of adaptive systems
Social network inference of smartphone users based on information diffusion models
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part II
Influence relation estimation based on lexical entrainment in conversation
Speech Communication
Discovering latent influence in online social activities via shared cascade poisson processes
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
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Online social sharing sites are becoming very popular nowadays among Web users, who use these sites to share their favourite items and to discover interesting and useful items from other users. While an explicit social network is not necessarily present in these sites, it is still possible that users influence one another in the process of item adoption through various implicit mechanisms. In this paper, we study how we can capture the implicit influences among the users in a social sharing site. We propose a probabilistic model for user adoption behaviour, where we assume that when user adopts an item, he would pick a user and choose from the set of items that this user has adopted. By using the model, we estimate the probability that one user influences another user in the course of item adoption, based on the temporal adoption pattern of the users. We carry out empirical studies of the model on Delicious, a popular social bookmarking site. Experiments show that our model can be used to predict item adoption more accurately than using collaborative filtering techniques. We find that the strength of implicit influence various across different topics. We also show that our method is able to identify the influential users who are more likely to possess items interested by other users. Our model can be used to study the dynamics in a social sharing site and to complement collaborative filtering in recommendation systems.