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Twitter User Clustering Based on Their Preferences and the Louvain Algorithm

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Title:
Twitter User Clustering Based on Their Preferences and the Louvain Algorithm.
Authors: 
López Sánchez, Daniel; Revuelta Herrero, Jorge; de la Prieta Pintado, Fernando; Gil González, Ana B.; Dang, Cach
Book:
Trends in Practical Applications of Scalable Multi-Agent Systems, the PAAMS Collection. Advances in Intelligent Systems and Computing. Volume 473, pp. 349-356.

Publication date: 
07 June 2016
ISSN: 
2194-5357
ISBN: 
978-3-319-40158-4 (Print), 978-3-319-40159-1 (Online)
DOI
 10.1007/978-3-319-40159-1_29

BibTex

@conference { conference,
title = {Twitter User Clustering Based on Their Preferences and the Louvain Algorithm},
author = {López Sánchez, Daniel; Revuelta Herrero, Jorge; de la Prieta Pintado, Fernando; Gil González, Ana B.; Dang, Cach},
chapter = {Trends in Practical Applications of Scalable Multi-Agent Systems, the PAAMS Collection},
publisher = {Springer, Cham},
volume = {473},
pages = {349-356},
isbn = {978-3-319-40158-4 (Print), 978-3-319-40159-1 (Online)},
year = {2016}
}

XML

<inproceedings key='conf/López/07 June 2016' mdate='07 June 2016'>
<author>López Sánchez</author>
<author>Daniel; Revuelta Herrero</author>
<author>Jorge; de la Prieta Pintado</author>
<author>Fernando; Gil González</author>
<author>Ana B.; Dang</author>
<author>Cach</author>
<title>Twitter User Clustering Based on Their Preferences and the Louvain Algorithm</title>
<pages>349-356</pages>
<year>2016</year>
<booktitle>Trends in Practical Applications of Scalable Multi-Agent Systems, the PAAMS Collection</booktitle>
<ee>10.1007/978-3-319-40159-1_29</ee>
</inproceedings>

In this paper, a novel agent-based platform for Twitter user clustering is proposed. We describe how our system tracks the activity for a given topic in the social network and how to detect communities of users with similar political preferences by means of the Louvain Modularity. The quality of this clustering method is evaluated against a subset of human-labeled user profiles. Finally, we propose combining community detection with a force-directed graph algorithm to produce a visual representation of the political communities.

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