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Authors: Andreas Kanavos ; Isidoros Perikos ; Ioannis Hatzilygeroudis and Athanasios Tsakalidis

Affiliation: University of Patras, Greece

ISBN: 978-989-758-186-1

Keyword(s): Community Analysis, Graph Mining, Influential Community Detection, Sentiment Analysis, Tweet Emotion Recognition, User Influence.

Related Ontology Subjects/Areas/Topics: Social Media Analytics ; Society, e-Business and e-Government ; Web Information Systems and Technologies

Abstract: The analysis of social networks is a very challenging research area. A fundamental aspect concerns the detection of user communities, i.e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Detecting communities is of great importance in sociology, biology as well as computer science where systems are often represented as graphs. In this paper we present a novel methodology for community detection based on users’ emotional behavior. The methodology analyzes user’s tweets in order to determine their emotional behavior in Ekman emotional scale. We define two different metrics to count the influence of produced communities. Moreover, the weighted version of a modularity community detection algorithm is utilized. Our results show that our proposed methodology creates influential enough communities.

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Paper citation in several formats:
Kanavos, A.; Perikos, I.; Hatzilygeroudis, I. and Tsakalidis, A. (2016). Integrating User’s Emotional Behavior for Community Detection in Social Networks.In Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 1: SRIS, (WEBIST 2016) ISBN 978-989-758-186-1, pages 355-362. DOI: 10.5220/0005862703550362

@conference{sris16,
author={Andreas Kanavos. and Isidoros Perikos. and Ioannis Hatzilygeroudis. and Athanasios Tsakalidis.},
title={Integrating User’s Emotional Behavior for Community Detection in Social Networks},
booktitle={Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 1: SRIS, (WEBIST 2016)},
year={2016},
pages={355-362},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005862703550362},
isbn={978-989-758-186-1},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 1: SRIS, (WEBIST 2016)
TI - Integrating User’s Emotional Behavior for Community Detection in Social Networks
SN - 978-989-758-186-1
AU - Kanavos, A.
AU - Perikos, I.
AU - Hatzilygeroudis, I.
AU - Tsakalidis, A.
PY - 2016
SP - 355
EP - 362
DO - 10.5220/0005862703550362

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