Reputation Management in Online Social Networks - A New Clustering-based Approach

Sana Hamdi, Alda Lopes Gançarski, Amel Bouzeghoub, Sadok Ben Yahia

2017

Abstract

Trust and reputation management stands as a corner stone within the Online Social Networks (OSNs) since they ensure a healthy collaboration relationship among participants. Currently, most trust and reputation systems focus on evaluating the credibility of the users. The reputation systems in OSNs have as objective to help users to make difference between trustworthy and untrustworthy, and encourage honest users by rewarding them with high trust values. Computing reputation of one user within a network requires knowledge of trust degrees between the users. In this paper, we propose a new Clustering Reputation algorithm, called RepC, based on trusted network. This algorithm classifies the users of OSNs by their trust similarity such that most trustworthy users belong to the same cluster. We conduct extensive experiments on a real online social network dataset from Twitter. Experimental results show that our algorithm generates better results than do the pioneering approaches of the literature.

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Paper Citation


in Harvard Style

Hamdi S., Lopes Gançarski A., Bouzeghoub A. and Ben Yahia S. (2017). Reputation Management in Online Social Networks - A New Clustering-based Approach . In Proceedings of the 14th International Joint Conference on e-Business and Telecommunications - Volume 6: SECRYPT, (ICETE 2017) ISBN 978-989-758-259-2, pages 468-473. DOI: 10.5220/0006433104680473


in Bibtex Style

@conference{secrypt17,
author={Sana Hamdi and Alda Lopes Gançarski and Amel Bouzeghoub and Sadok Ben Yahia},
title={Reputation Management in Online Social Networks - A New Clustering-based Approach},
booktitle={Proceedings of the 14th International Joint Conference on e-Business and Telecommunications - Volume 6: SECRYPT, (ICETE 2017)},
year={2017},
pages={468-473},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006433104680473},
isbn={978-989-758-259-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 14th International Joint Conference on e-Business and Telecommunications - Volume 6: SECRYPT, (ICETE 2017)
TI - Reputation Management in Online Social Networks - A New Clustering-based Approach
SN - 978-989-758-259-2
AU - Hamdi S.
AU - Lopes Gançarski A.
AU - Bouzeghoub A.
AU - Ben Yahia S.
PY - 2017
SP - 468
EP - 473
DO - 10.5220/0006433104680473