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The challenge of improving credibility of user-generated content in online social networks

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Auteur
Haralabopoulos G., Anagnostopoulos I., Zeadally S.
Date
2016
Language
en
DOI
10.1145/2899003
Sujet
Data mining
Credibility
Information exchanges
Information quality
On-line social networks
Online social networks (OSNs)
Quality assessment model
Real-time data mining
User-generated content
Social networking (online)
Association for Computing Machinery
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Résumé
In every environment of information exchange, Information Quality (IQ) is considered one of the most important issues. Studies in Online Social Networks (OSNs) analyze a number of related subjects that span both theoretical and practical aspects, from data quality identification and simple attribute classification to quality assessment models for various social environments. Among several factors that affect information quality in online social networks is the credibility of user-generated content. To address this challenge, some proposed solutions include community-based evaluation and labeling of user-generated content in terms of accuracy, clarity, and timeliness, along with well-established real-time data mining techniques. © 2016 ACM.
URI
http://hdl.handle.net/11615/73896
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