Longitudinal Modeling of Social Media with Hawkes Process based on Users and Networks

Srijith, P K and Lukasik, M and Bontcheva, K and Cohn, T (2017) Longitudinal Modeling of Social Media with Hawkes Process based on Users and Networks. In: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 31 July - 03 August, 2017, Sydney, Australia.

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Abstract

Online social networks provide a platform for sharing information at an unprecedented scale. Users generate information which propagates across the network resulting in information cascades. In this paper, we study the evolution of information cascades in Twitter using a point process model of user activity. We develop several Hawkes process models considering various properties including conversational structure, users’ connections and general features of users including the textual information, and show how they are helpful in modeling the social network activity. We consider low-rank embeddings of users and user features, and learn the features helpful in identifying the influence and susceptibility of users. Evaluation on Twitter data sets associated with civil unrest shows that incorporating richer properties improves the performance in predicting future activity of users and memes.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computer science > Computer programming, programs, data
Computer science > Special computer methods
Divisions: Department of Computer Science & Engineering
Depositing User: Team Library
Date Deposited: 14 Jun 2017 10:41
Last Modified: 14 Jun 2017 10:41
URI: http://raiith.iith.ac.in/id/eprint/3234
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