GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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
Passage time distributions in large Markov chains
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Mining knowledge-sharing sites for viral marketing
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
An analysis of Internet chat systems
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Algorithms for estimating relative importance in networks
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
IEEE Transactions on Knowledge and Data Engineering
Personalized recommendation driven by information flow
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Probability Models, Ninth Edition
Introduction to Probability Models, Ninth Edition
Identifying opinion leaders in the blogosphere
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Prediction of Information Diffusion Probabilities for Independent Cascade Model
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
Mining social networks using heat diffusion processes for marketing candidates selection
Proceedings of the 17th ACM conference on Information and knowledge management
Social influence and the diffusion of user-created content
Proceedings of the 10th ACM conference on Electronic commerce
A fuzzy biclustering algorithm for social annotations
Journal of Information Science
Ordering innovators and laggards for product categorization and recommendation
Proceedings of the third ACM conference on Recommender systems
Learning Continuous-Time Information Diffusion Model for Social Behavioral Data Analysis
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Learning influence probabilities in social networks
Proceedings of the third ACM international conference on Web search and data mining
Determining content power users in a blog network
Proceedings of the 3rd Workshop on Social Network Mining and Analysis
Prediction of social bookmarking based on a behavior transition model
Proceedings of the 2010 ACM Symposium on Applied Computing
Capturing implicit user influence in online social sharing
Proceedings of the 21st ACM conference on Hypertext and hypermedia
Extraction, characterization and utility of prototypical communication groups in the blogosphere
ACM Transactions on Information Systems (TOIS)
Group dynamics in discussing incidental topics over online social networks
IEEE Network: The Magazine of Global Internetworking
Social Network Analysis and Mining for Business Applications
ACM Transactions on Intelligent Systems and Technology (TIST)
Interaction-driven opinion dynamics in online social networks
Proceedings of the First Workshop on Social Media Analytics
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
A data-based approach to social influence maximization
Proceedings of the VLDB Endowment
Content based social behavior prediction: a multi-task learning approach
Proceedings of the 20th ACM international conference on Information and knowledge management
Forward or ignore: user behavior analysis and prediction on microblogging
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Prediction of retweet cascade size over time
Proceedings of the 21st ACM international conference on Information and knowledge management
The Dynamics of Content Popularity in Social Media
International Journal of Data Warehousing and Mining
Meme ranking to maximize posts virality in microblogging platforms
Journal of Intelligent Information Systems
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
Finding contexts of social influence in online social networks
Proceedings of the 7th Workshop on Social Network Mining and Analysis
Diffusion-aware personalized social update recommendation
Proceedings of the 7th ACM conference on Recommender systems
A probability based algorithm for influence maximization in social networks
Proceedings of the 5th Asia-Pacific Symposium on Internetware
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Information flows in a network where individuals influence each other. The diffusion rate captures how efficiently the information can diffuse among the users in the network. We propose an information flow model that leverages diffusion rates for: (1) prediction . identify where information should flow to, and (2) ranking . identify who will most quickly receive the information. For prediction, we measure how likely information will propagate from a specific sender to a specific receiver during a certain time period. Accordingly a rate-based recommendation algorithm is proposed that predicts who will most likely receive the information during a limited time period. For ranking, we estimate the expected time for information diffusion to reach a specific user in a network. Subsequently, a DiffusionRank algorithm is proposed that ranks users based on how quickly information will flow to them. Experiments on two datasets demonstrate the effectiveness of the proposed algorithms to both improve the recommendation performance and rank users by the efficiency of information flow.