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Authors: Fabio Cozzolino 1 ; Vincenzo Moscato 1 ; Antonio Picariello 1 and Giancarlo Sperli 2

Affiliations: 1 DIETI, University of Naples Federico II and Italy ; 2 ITEM National Lab, CINI, Naples and Italy

Keyword(s): Smart-Phone Addiction, Knowledge Discovery, Social Network Analysis, Community Detection.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Data Analytics ; Data Engineering ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems

Abstract: In this paper, we present a novel approach for Smart-Phone Addiction recognition that leverages community detection algorithms from the Social Network Analysis (SNA) theory. Our basic idea is to model data concerning users’ behavior while they are using mobile devices as a particular social graph, discovering by means of SNA facilities patterns that better identify users with a high predisposition to smart phone addiction. Eventually, several experiments on a sample of users monitored for several weeks have been carried out to verify effectiveness of the proposed approach in correctly recognizing the related addiction degree.

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Paper citation in several formats:
Cozzolino, F.; Moscato, V.; Picariello, A. and Sperli, G. (2019). A Community Detection Approach for Smart-Phone Addiction Recognition. In Proceedings of the 8th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-377-3; ISSN 2184-285X, SciTePress, pages 53-64. DOI: 10.5220/0007839100530064

@conference{data19,
author={Fabio Cozzolino. and Vincenzo Moscato. and Antonio Picariello. and Giancarlo Sperli.},
title={A Community Detection Approach for Smart-Phone Addiction Recognition},
booktitle={Proceedings of the 8th International Conference on Data Science, Technology and Applications - DATA},
year={2019},
pages={53-64},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007839100530064},
isbn={978-989-758-377-3},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Data Science, Technology and Applications - DATA
TI - A Community Detection Approach for Smart-Phone Addiction Recognition
SN - 978-989-758-377-3
IS - 2184-285X
AU - Cozzolino, F.
AU - Moscato, V.
AU - Picariello, A.
AU - Sperli, G.
PY - 2019
SP - 53
EP - 64
DO - 10.5220/0007839100530064
PB - SciTePress

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