This study aims to investigate how users assess the credibility of information on social question-and-answer (Q&A) platforms. This study builds on a social Q&A-specific Web credibility framework (Choi et al., 2023), integrating a two-dimensional model of credibility – trustworthiness and expertise (Hovland et al., 1953) – and three types of Web credibility cues and heuristics – author or community, content and design (Fogg, 2003).
Using online survey data from 598 users, the authors used exploratory factor analysis to identify ten credibility criteria across three categories: author or community, content and design. One-sample t-tests assessed the perceived importance of these criteria, and multiple regression analyses examined their associations with two core credibility dimensions – trustworthiness and expertise – while controlling for user characteristics.
Although the identified criteria were rated highly overall in conceptual importance (M = 3.92), only six – community reputation, appropriate design, moderation, engaging design, reference reliability and decency – were significantly associated with perceived trustworthiness, expertise or both. In contrast, traditionally valued criteria related to answer quality or author characteristics had limited predictive power. These findings support a refined, empirically grounded eight-criterion framework for credibility in social Q&A environments.
This study offers a data-driven update to a 21-criterion credibility model, identifying the most influential criteria in terms of conceptual importance and applicability in evaluating the trustworthiness and expertise of information on peer-based, collaborative platforms. Also, it suggests potential to extend the framework to emerging environments, such as generative artificial intelligence, where criteria like reference reliability remain relevant.
