Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
The dynamics of viral marketing
ACM Transactions on the Web (TWEB)
Social influence and the diffusion of user-created content
Proceedings of the 10th ACM conference on Electronic commerce
Predicting the popularity of online content
Communications of the ACM
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Outtweeting the twitterers - predicting information cascades in microblogs
WOSN'10 Proceedings of the 3rd conference on Online social networks
Modeling Information Diffusion in Implicit Networks
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Everyone's an influencer: quantifying influence on twitter
Proceedings of the fourth ACM international conference on Web search and data mining
Predicting popular messages in Twitter
Proceedings of the 20th international conference companion on World wide web
What's in a hashtag?: content based prediction of the spread of ideas in microblogging communities
Proceedings of the fifth ACM international conference on Web search and data mining
The structure of online diffusion networks
Proceedings of the 13th ACM Conference on Electronic Commerce
Information diffusion and external influence in networks
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Prediction of retweet cascade size over time
Proceedings of the 21st ACM international conference on Information and knowledge management
Characterizing and curating conversation threads: expansion, focus, volume, re-entry
Proceedings of the sixth ACM international conference on Web search and data mining
Analyzing and predicting viral tweets
Proceedings of the 22nd international conference on World Wide Web companion
Exploring Image Virality in Google Plus
SOCIALCOM '13 Proceedings of the 2013 International Conference on Social Computing
The bursty dynamics of the Twitter information network
Proceedings of the 23rd international conference on World wide web
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On many social networking web sites such as Facebook and Twitter, resharing or reposting functionality allows users to share others' content with their own friends or followers. As content is reshared from user to user, large cascades of reshares can form. While a growing body of research has focused on analyzing and characterizing such cascades, a recent, parallel line of work has argued that the future trajectory of a cascade may be inherently unpredictable. In this work, we develop a framework for addressing cascade prediction problems. On a large sample of photo reshare cascades on Facebook, we find strong performance in predicting whether a cascade will continue to grow in the future. We find that the relative growth of a cascade becomes more predictable as we observe more of its reshares, that temporal and structural features are key predictors of cascade size, and that initially, breadth, rather than depth in a cascade is a better indicator of larger cascades. This prediction performance is robust in the sense that multiple distinct classes of features all achieve similar performance. We also discover that temporal features are predictive of a cascade's eventual shape. Observing independent cascades of the same content, we find that while these cascades differ greatly in size, we are still able to predict which ends up the largest.