Background: The phenomenon of review manipulation and fake reviews has gained Information Systems (IS) scholars’ attention during recent years. Scholarly research in this domain has delved into the causes and consequences of review manipulation. However, we find that the findings are diverse, and the studies do not portray a systematic approach. This study synthesizes the findings from a multidisciplinary perspective and presents an integrated framework to understand the mechanism of review manipulation.
Method: The study reviews 88 relevant articles on review manipulation spanning a decade and a half. We adopted an iterative coding approach to synthesizing the literature on concepts and categorized them independently into potential themes.
Results: We present an integrated framework that shows the linkages between the different themes, namely, the prevalence of manipulation, impact of manipulation, conditions and choice for manipulation decision, characteristics of fake reviews, models for detecting spam reviews, and strategies to deal with manipulation. We also present the characteristics of review manipulation and cover both operational and conceptual issues associated with the research on this topic.
Conclusions: Insights from the study will guide future research on review manipulation and fake reviews. The study presents a holistic view of the phenomenon of review manipulation. It informs various online platforms to address fake reviews towards building a healthy and sustainable environment.
Ansari, Sana and Gupta, Sumeet
"Review Manipulation: Literature Review, and Future Research Agenda,"
Pacific Asia Journal of the Association for Information Systems: Vol. 13:
1, Article 4.
Available at: https://aisel.aisnet.org/pajais/vol13/iss1/4