2019•Journal of the Association for Information SystemsRequires access

Towards a Credibility Analysis Model for Online Reviews

Ehsan Abedin, Antonette Mendoza, Shanika A. Karunasekera

Abstract

In digital transformations era, user-generated reviews have become important sources of information, and they play a significant role in users’ decision-making process. However, the overwhelming number of online reviews with unknown reviewers has made it difficult for users to find credible information. This paper conceptualizes a credibility analysis model for online reviews by synthesizing the related literature and using the Heuristic-Systematic Model (HSM). The credibility analysis model demonstrates factors affecting online reviews credibility (e.g., argument strength, review objectivity, review sidedness, internal consistency, reviewer credibility, external consistency, information rating, and structural factors). Moreover, the proposed model examines the moderating role of product/service types on the relationships between reviews credibility and its antecedents. To refine the model and our hypotheses, we plan to interview users of online reviews. Then, the hypotheses and model will be tested through a quantitative approach.

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Key concepts: Credibility, Consistency (knowledge bases), Computer science, Objectivity (philosophy), Source credibility, Argument (complex analysis), Data science, Process (computing)