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ZENODO
Dataset . 2018
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2018
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2018
License: CC BY
Data sources: Datacite
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Community-Based Event Detection in Temporal Networks

Authors: Pablo Moriano; Jorge Finke; Yong-Yeol Ahn;

Community-Based Event Detection in Temporal Networks

Abstract

P.M. was supported by Cisco Research under grant #591000. 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.

This dataset contains daily tweets ids during April 2013. This is provided to facilitate reproducibility of results presented in the following paper: Pablo Moriano, Jorge Finke, and Yong-Yeol Ahn. "Community-Based Event Detection in Temporal Networks." Scientific Reports 9, 4358, 2019. DOI: https://doi.org/10.1038/s41598-019-40137-0 These data are provided for non-commercial purposes only. If you use this dataset for research, please be sure to cite the above paper.

Keywords

Temporal networks, event detection, community structure, information diffusion, Enron, Twitter, Boston marathon

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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