Web Credibility Assessments in the Context of Social Q&A Sites

Funded by UWM to explore cues and heuristics employed users in their credibility assessments of information on social Q&A sites. 2021 ($4,887)

Project Description

Social question-and-answer (Q&A) sites are a type of social media that allows users to ask and answer questions, evaluate content submitted by others, and view the community’s aggregate assessment of which questions, answers, and users are best. Characterized by its content-focused and collaborative nature, social Q&A sites are considered a useful platform for information seekers to express their information needs as questions in natural language, as opposed to using keywords to create search queries, and obtain answers that are based on the community’s collective knowledge. Despite the popularity of social media and the potential of social Q&A sites as an online information source, relatively less research has focused on credibility issues in social Q&A sites. The current project aims to fill this gap in the literature by exploring which criteria are employed by users to judge the credibility of information on social Q&A sites (e.g., answers) and what user characteristics contribute to the variability of web credibility assessment on social Q&A sites.

As an effective means for collecting a large sample of motivated participants, an online survey will be conducted on a crowdsourced survey site, Amazon Mechanical Turk (MTurk; https://www.mturk.com). The target sample size is 500 complete responses. The survey data will be used to compile existing measurements of perceived credibility of information on social Q&A sites, identify the underlying structure of the construct, and test these components in a hierarchical linear model. The analysis results will allow developing an information system (platform) type-specific model of web credibility assessment, which can serve as a useful theoretical framework for researchers and developers. Findings of the research will be distributed as a conference presentation and journal article in the field of information science.

Research Team

  • Wonchan Choi, PI, Assistant Professor, University of Wisconsin-Milwaukee (UWM) iSchool
  • Hyun Seung Lee, RA, PhD Student, UWM iSchool

Funding Information

  • Program: UWM Research Assistance Fund
  • Period: 2021
  • Funds $4,887