2012/01/11 by Andrey Kan, Kan, Andrey, Jeffrey Chan +9
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #Data Visualization and Analytics #FOS: Computer and information sciences #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI) #Time Series Analysis and Forecasting
paper · pdf · doi:10.48550/arxiv.1201.2277
openalex publication_date 2012/01/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Online forums are rich sources of information about user communication activity over time. Finding temporal patterns in online forum communication threads can advance our understanding of the dynamics of conversations. The main challenge of temporal analysis in this context is the complexity of forum data. There can be thousands of interacting users, who can be numerically described in many different ways. Moreover, user characteristics can evolve over time. We propose an approach that decouples temporal information about users into sequences of user events and inter-event times. We develop a new feature space to represent the event sequences as paths, and we model the distribution of the inter-event times. We study over 30,000 users across four Internet forums, and discover novel patterns in user communication. We find that users tend to exhibit consistency over time. Furthermore, in our feature space, we observe regions that represent unlikely user behaviors. Finally, we show how to derive a numerical representation for each forum, and we then use this representation to derive a novel clustering of multiple forums.