Combating Survey Bots in Online Research: An Integrative Literature Review of Insights and Strategies 

Abstract

Survey bots pose a major challenge to the integrity and quality of online data. Even though information systems (IS) literature has increasingly recognized bot infiltration, recommendations on mitigation strategies remain largely confined to the disparate academic domains in which researchers studied bots. We use the integrated literature review (ILR) method to analyze relevant studies published from 2010 through 2022 to provide an overview of the extant research on survey bots, identify areas that warrant further scholarship, and highlight state-of-the-art techniques for bot management. We found that the literature on survey bots is fragmented and lacks a set of generalized recommendations for online survey research across contexts. Thus, we consolidate cross-disciplinary themes and propose best practices to researchers and practitioners to combat survey bots. In doing so, our study can serve as a reference point for scholars who investigate this emerging phenomenon. We also provide a decision tree to help scholars and practitioners to use bot management techniques in their online surveys.

Keywords: survey, bots, prevention, detection, online survey