Detecting Large Reshare Cascades in Social Networks
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[1] Jure Leskovec,et al. SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity , 2015, KDD.
[2] Jure Leskovec,et al. Patterns of temporal variation in online media , 2011, WSDM '11.
[3] Prem Melville,et al. Supervised Rank Aggregation for Predicting Influencers in Twitter , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.
[4] P. Young,et al. Time series analysis, forecasting and control , 1972, IEEE Transactions on Automatic Control.
[5] Mingxuan Sun,et al. A hazard based approach to user return time prediction , 2014, KDD.
[6] Jure Leskovec,et al. Modeling Information Diffusion in Implicit Networks , 2010, 2010 IEEE International Conference on Data Mining.
[7] Christos Faloutsos,et al. Rise and fall patterns of information diffusion: model and implications , 2012, KDD.
[8] Ravi Kumar,et al. On the Bursty Evolution of Blogspace , 2003, WWW '03.
[9] Dimitrios Gunopulos,et al. Finding effectors in social networks , 2010, KDD.
[10] Didier Sornette,et al. Robust dynamic classes revealed by measuring the response function of a social system , 2008, Proceedings of the National Academy of Sciences.
[11] Herbert W. Hethcote,et al. The Mathematics of Infectious Diseases , 2000, SIAM Rev..
[12] Éva Tardos,et al. Maximizing the Spread of Influence through a Social Network , 2015, Theory Comput..
[13] Michalis Faloutsos,et al. Threshold conditions for arbitrary cascade models on arbitrary networks , 2011, 2011 IEEE 11th International Conference on Data Mining.
[14] References , 1971 .
[15] Andreas Krause,et al. Cost-effective outbreak detection in networks , 2007, KDD '07.
[16] Madhav V. Marathe,et al. EpiSimdemics: an efficient algorithm for simulating the spread of infectious disease over large realistic social networks , 2008, HiPC 2008.
[17] Zhoujun Li,et al. Burst Time Prediction in Cascades , 2015, AAAI.
[18] Jacob Goldenberg,et al. Talk of the Network: A Complex Systems Look at the Underlying Process of Word-of-Mouth , 2001 .
[19] Jure Leskovec,et al. Inferring networks of diffusion and influence , 2010, KDD.
[20] K. Hornik,et al. Unbiased Recursive Partitioning: A Conditional Inference Framework , 2006 .
[21] Tudor Dumitras,et al. Spatio-temporal mining of software adoption & penetration , 2013, 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013).
[22] Charu C. Aggarwal,et al. Content-centric flow mining for influence analysis in social streams , 2013, CIKM.
[23] Fei Wang,et al. Cascading outbreak prediction in networks: a data-driven approach , 2013, KDD.
[24] P. Grambsch,et al. A Package for Survival Analysis in S , 1994 .
[25] Rediet Abebe. Can Cascades be Predicted? , 2014 .
[26] Christos Faloutsos,et al. Patterns of Cascading Behavior in Large Blog Graphs , 2007, SDM.
[27] Fei Wang,et al. From Micro to Macro: Uncovering and Predicting Information Cascading Process with Behavioral Dynamics , 2015, 2015 IEEE International Conference on Data Mining.
[28] A. J. Hall. Infectious diseases of humans: R. M. Anderson & R. M. May. Oxford etc.: Oxford University Press, 1991. viii + 757 pp. Price £50. ISBN 0-19-854599-1 , 1992 .
[29] Christos Faloutsos,et al. Fractional Immunization in Networks , 2013, SDM.
[30] I. Langner. Survival Analysis: Techniques for Censored and Truncated Data , 2006 .
[31] Bernhard Schölkopf,et al. Modeling Information Propagation with Survival Theory , 2013, ICML.
[32] Madhav V. Marathe,et al. EpiSimdemics: An efficient algorithm for simulating the spread of infectious disease over large realistic social networks , 2008, 2008 SC - International Conference for High Performance Computing, Networking, Storage and Analysis.
[33] E. Rogers,et al. Diffusion of Innovations, 5th Edition , 2003 .
[34] Ambuj K. Singh,et al. Beyond Models: Forecasting Complex Network Processes Directly from Data , 2015, WWW.
[35] Scott Counts,et al. Predicting the Speed, Scale, and Range of Information Diffusion in Twitter , 2010, ICWSM.
[36] Suman Nath,et al. ThermoCast: a cyber-physical forecasting model for datacenters , 2011, KDD.
[37] Michalis Faloutsos,et al. Gelling, and melting, large graphs by edge manipulation , 2012, CIKM.
[38] Bernardo A. Huberman,et al. Predicting the popularity of online content , 2008, Commun. ACM.
[39] Justin Cheng,et al. Rumor Cascades , 2014, ICWSM.