A Multi-Criteria Decision Making approach based on the Choquet integral for assessing the credibility of User-Generated Content
作者： Gabriella Pasi , Marco Viviani , Alexandre Carton
DOI: 10.1016/J.INS.2019.07.037
关键词:
摘要: Abstract The Social Web promotes social interactions among people through 2.0 technologies. In this context, User-Generated Content (UGC) spreads across media platforms in the absence of traditional intermediaries that can verify both believability content and reliability sources generated it. For reason, problem how to assess credibility UGC is receiving nowadays increasing attention. literature, several approaches have tackled issue mainly as a classification problem, by categorizing information into genuine fake. majority proposed solutions follows data-driven approach, employing supervised or semi-supervised machine learning techniques act on multiple features related credibility. Despite its effectiveness, however, may present some possible drawbacks, including data-dependency inscrutability contribution single interacting final process. paper, Multi-Criteria Decision Making approach proposed, aimed UGC. A given item (alternative) evaluated with respect considered (criteria) based prior domain knowledge, where an overall estimate obtained means suitable model-driven aggregation operators. allows classify credible non-credible one, also be used provide ranking alternatives To consider features, Choquet integral employed.
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