Community-Based Event Detection in Temporal Networks

Pablo Moriano; Jorge Finke; Yong Yeol Ahn

doi:10.1038/s41598-019-40137-0

Community-Based Event Detection in Temporal Networks

Pablo Moriano, Jorge Finke, Yong Yeol Ahn

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

We propose a method for detecting large events based on the structure of temporal communication networks. Our method is motivated by findings that viral information spreading has distinct diffusion patterns with respect to community structure. Namely, we hypothesize that global events trigger viral information cascades that easily cross community boundaries and can thus be detected by monitoring intra- and inter-community communications. By comparing the amount of communication within and across communities, we show that it is possible to detect events, even when they do not trigger a significantly larger communication volume. We demonstrate the effectiveness of our method using two examples—the email communication network of Enron and the Twitter communication network during the Boston Marathon bombing.

Original language	English
Article number	4358
Journal	Scientific Reports
Volume	9
Issue number	1
DOIs	https://doi.org/10.1038/s41598-019-40137-0
State	Published - Dec 1 2019
Externally published	Yes

Funding

We thank Filippo Menczer for helping us analyze the Twitter data. P.M. was supported by Cisco Research under grant #591000. P.M. thanks L. Jean Camp and Steven Rich for their guidance. J.F. was supported in part by the Center of Excellence and Appropriation in Big Data and Data Analytics (CAOBA) and the Colombian Administrative Department of Science, Technology and Innovation (COLCIENCIAS) under grant number FP44842. Y.-Y.A. is supported by the Defense Advanced Research Projects Agency (DARPA), contract W911NF-17-C-0094. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Cisco, COLCIENCIAS, DARPA or the U.S. Government.

Funders	Funder number
Cisco Research
Defense Advanced Research Projects Agency	W911NF-17-C-0094
Cisco Systems	591000
Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)	FP44842

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10.1038/s41598-019-40137-0

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Community-Based Event Detection in Temporal Networks

Abstract

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