The influence of user profile enrichment on buzz spread in social media experiments on delicious

The influence of user profile enrichment on buzz spread in social media experiments on delicious

Manel Mezghani André Péninou Florence Sèdes Sirinya On-At Arnaud Quirin Marie-Françoise Canut

Université de Sfax, laboratoire MIRACL, Sfax, Tunisie

IRIT, Université de Toulouse, CNRS, INPT, UPS, UT1, UT2J, France

Corresponding Author Email: 
{mezghani.manel, aquirin}@gmail.com, {andre.peninou, florence.sedes, sirinya.on-at}@irit.fr, marie-francoise.canut@univ-tlse2.fr
Page: 
67-81
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DOI: 
https://doi.org/10.3166/ISI.21.4.67-81
Received: 
N/A
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Accepted: 
N/A
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Published: 
31 August 2016
| Citation
Abstract: 

The user is the main contributor for creating information in social media and is influenced by the information shared through such networks. There are so-called “buzz”, which is a technique to cause a stir around a piece of information (fact or rumour) so that several users will be interested in simultaneously, can be defined as a popular piece of information in a specific time. We are interested in studying the influence of the dynamic user profile enrichment (Mezghani et al., 2014) on the buzz propagation and we experiment it to the social network Delicious. Delicious contains social annotations (tags) provided by users and that contribute to influence other users to follow some information or to use them. Our study is grounded on the following methodology: 1) we analyse the propagation of tags considered as buzz through time 2) we apply the dynamic user profile enrichment and we analyse the influence of this enrichment in the buzz propagation, 3) we analyse if the enrichment approach anticipates the buzz propagation. Thus, we show interest, during profile enrichment, of filtering the information in order to propose relevant results to the user and avoid “bad” recommendations.

Keywords: 

user profile, enrichment, tag, resource, buzz, time

1. Introduction
2. Aperçu de l’approche d’enrichissement dynamique
3. Étude de cas sur un ensemble de données de Delicious sur la propagation de buzz
4. Conclusion
Remerciements
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