Collaborative Content-Based Method for Estimating User Reputation in Online Forums

Amine Abdaoui 1 Jérôme Azé 1 Sandra Bringay 1, 2 Pascal Poncelet 1
1 ADVANSE - ADVanced Analytics for data SciencE
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
2 UM3 - Université Paul-Valéry - Montpellier 3
Abstract : Collaborative ratings of forum posts have been successfully applied in order to infer the reputations of forum users. Famous websites such as Slashdot or Stack Exchange allow their users to score messages in order to evaluate their content. These scores can be aggregated for each user in order to compute a reputation value in the forum. However, explicit rating functionalities are rarely used in many online communities such as health forums. At the same time, the textual content of the messages can reveal a lot of information regarding the trust that users have in the posted information. In this work, we propose to use these hidden expressions of trust in order to estimate user reputation in online forums.
Keywords : social networks online forums reputation Trust
Document type :
Conference papers
Complete list of metadatas

Cited literature [9 references]  Display  Hide  Download
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01222961
Contributor : Amine Abdaoui <>
Submitted on : Saturday, October 31, 2015 - 3:49:44 PM
Last modification on : Thursday, June 6, 2019 - 2:46:58 PM
Long-term archiving on : Friday, April 28, 2017 - 6:30:43 AM

File

WISE_2015_150.pdf
Files produced by the author(s)

Identifiers

Collections

ADVANSE | LIRMM | MIPS | UNIV-MONTPELLIER | UNIV-MONTP3

Citation

Amine Abdaoui, Jérôme Azé, Sandra Bringay, Pascal Poncelet. Collaborative Content-Based Method for Estimating User Reputation in Online Forums. WISE: Web Information Systems Engineering, Nov 2015, Miami, United States. pp.292-299, ⟨10.1007/978-3-319-26187-4_26⟩. ⟨lirmm-01222961⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

206

Files downloads

437

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD