SMILE: An Informality Classification Tool for Helping to Assess Quality and Credibility in Web 2.0 Texts

Abstract

The data made available by Web 2.0 applications such as social networks, on-line chats or blogs have give access to multiples sources of information. Due to this dramatic increase in available information, the perception of quality and credibility plays an important role in social media, thus making necessary to discard low quality and uninteresting content. Moreover, the informal features of Web 2.0 texts such as emoticons, typos, slang or loss of formatting impact negatively on user perception regarding content quality and credibility. For this reason, this paper proposes the SMILE system, a novel unsupervised real-time tool for assessing user-generated content quality and credibility using informality levels. As a test case, we focus on Yahoo! Answers, a relevant Web 2.0 application by its amount of users, content and textual diversity. The results of our study show that informality analysis can be used as criteria to help assess the credibility and quality of Web 2.0 information sources.