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Event Detection by Change Tracking on Community Structure of Temporal Networks
Date
2018-08-31
Author
Aktunc, Riza
Toroslu, İsmail Hakkı
Karagöz, Pınar
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Event detection is a popular research problem, aiming to detect events from online data sources with least possible delay. Most of the previous work focus on analyzing textual content such as social media postings to detect happenings. In this work, we consider event detection as a change detection problem in network structure, and propose a method that detects change in community structure extracted from communication network. We study three versions of the method based on different change models. Experimental analysis on benchmark data set reveals that change in the community can be used as an indication of an event.
Subject Keywords
Event detection
,
Temporal network
,
Community detection
,
Network features
,
Change
URI
https://hdl.handle.net/11511/52701
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Department of Computer Engineering, Conference / Seminar
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Event detection is a popular research problem aiming to detect events from various data sources, such as climate records, traffic data, news texts, social media postings or social interaction patterns. In this work, event detection is studied on social interaction and communication data via tracking changes in community structure, communication trends, and graph embeddings. With this aim, various community structure, communication trend, and graph embedding based event detection methods are proposed. Additi...
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R. Aktunc, İ. H. Toroslu, and P. Karagöz, “Event Detection by Change Tracking on Community Structure of Temporal Networks,” 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52701.