An ensemble method for the credibility assessment of user-generated content
Julien Fontanarava, Gabriella Pasi, Marco Viviani · Proceedings of the International Conference on Web Intelligence · 2017
The Social Web supports and fosters social interactions by means of different social media, which allow the spread of the so called User-Generated Content (UGC). In this context, characterized by the absence of trusted third parties that verify the reliability of the sources and the believability of the content generated, the issue of assessing the credibility of the information diffused by means of social media is receiving increasing attention. In the literature, this issue has been mainly tackled as a classification problem; information is categorized into genuine and fake, usually by implementing or applying classifiers that consider multiple kinds of features (mainly textual and non-textual) to be evaluated in terms of credibility.