Perceptions of answer quality in an online technical question and answer forum
Kerry Hart, Anita Sarma · 2014
Software developers are used to seeking information from authoritative texts, such as a technical manuals, or from experts with whom they are familiar. Increasingly, developers seek information in online question and answer forums, where the quality of the information is variable. To a novice, it may be challenging to filter good information from bad. Stack Overflow is a Q&A forum that introduces a social reputation element: users rate the quality of post-ed answers, and answerers can accrue points and rewards for writing answers that are rated highly by their peers. A user that consistently authors good answers will develop a good ‘reputation’ as recorded by these points. While this system was designed with the intent to incentivize high-quality answers, it has been suggested that information seekers—and particularly technical novices—may rely on the social reputation of the answerer as a proxy for answer quality. In this paper, we investigate the role that this social factor—as well as other answer characteristics—plays in the information filtering process of technical novices in the context of Stack Over-flow. The results of our survey conducted on Amazon.com’s Mechanical Turk indicate that technical novices assess information quality based on the intrinsic qualities of the answer, such as presentation and content, suggesting that novices are wary to rely on social cues in the Q&A context.