When Question-and-Answer Consistency Matters: The Effects of Sentiment and Thematic Consistency on Answer Helpfulness

Online social Q&A communities have gained traction for their role in disseminating high-value information in the form of question-and-answer. Although the factors influencing answer helpfulness in these communities have been widely discussed, the mechanism of how consistency between questions and answers affects answer helpfulness remains unclear. From a congruence perspective, this study integrates text mining and sentiment mining to offer a novel framework of what constitutes the helpfulness of an answer within online social Q&A communities. Based on the Heuristic-Systematic Model, we employ sentiment consistency and thematic consistency as heuristic and systematic factors, respectively. We also explore the moderating effects of cognitive social identity, affective social identity, and relational identity on the relationship between consistency factors and answer usefulness from the perspective of identity theory. The results indicated that while thematic consistency has a positive impact on answer helpfulness, sentiment consistency has a negative impact. Moreover, different identities have varied effects in various situations.