Event Detection on Communities: Tracking the Change in Community Structure within Temporal Communication Networks

Date

2020-01-01

Author

Aktunç, Rıza
Toroslu, İsmail Hakkı
Karagöz, Pınar

Metadata

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In this work, we focus on social interactions in communities in order to detect events. There are several previous efforts for the event detection problem based on analyzing the change in the network structure in terms of the overall network features. However, in this work, event detection is considered as a problem of change detection in community structures. Particularly, communities extracted from communication network are focused on, and various versions of the community change detection methods are developed using different models. Furthermore, ensemble methods combining the change models are proposed and their event detection performances are analyzed, as well. Experiments conducted on benchmark data set show that community change can be used as an indicator of event, and ensemble model further improves the event detection performance.

Subject Keywords

Event detection, Temporal network, Community detection, Network features, Change tracking, Ensemble model

URI

https://link.springer.com/chapter/10.1007/978-3-030-33698-1_5
https://hdl.handle.net/11511/83370

Relation

Putting Social Media and Networking Data in Practice for Education, Planning, Prediction and Recommendation

Collections

Department of Computer Engineering, Book / Book chapter

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Citation Formats

R. Aktunç, İ. H. Toroslu, and P. Karagöz, Event Detection on Communities: Tracking the Change in Community Structure within Temporal Communication Networks. 2020, p. 96.