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Yanfeng Xu, Sarah Pace, Jaeseung Kim, Aidyn Iachini, L Bailey King, Theresa Harrison, Dana DeHart, Sue E Levkoff, Teri A Browne, Ashlee A Lewis, Gina M Kunz, Melissa Reitmeier, R Karen Utter, Melissa Simone, Threats to Online Surveys: Recognizing, Detecting, and Preventing Survey Bots, Social Work Research, Volume 46, Issue 4, December 2022, Pages 343–350, https://doi.org/10.1093/swr/svac023
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While securing data integrity has been a growing issue with online surveys for over a decade, recent cyber threats to online research, particularly survey bots, have escalated dramatically (Griffin et al., 2022; Pozzar et al., 2020; Storozuk et al., 2020). Survey bots, also known as automated form fillers, are computer programs that fill out web-based surveys with random responses (Howell, n.d.). While the exact programs and processes that bot programmers use to code and deploy bots remain largely unknown, they likely mirror those used in chatbot programming common in various customer service sections of businesses and websites (Kollanyi, 2016).
There is an increased risk of bots filling out online surveys, especially when monetary incentives are offered (Griffin et al., 2022; Nosen & Woody, 2008). At times, studies that do not offer incentives become targets to improve language processing for bots to use on future studies that do offer incentives. In addition, due to the anonymity of respondents and researchers’ lack of individual contact with survey participants, it can be difficult to distinguish whether responses to online surveys are from humans or bots (Bowen et al., 2008; Mitchell et al., 2020). Furthermore, bot programs become more sophisticated the longer they are deployed, which makes it harder for researchers, particularly those without prior knowledge of bots, to recognize, detect, and prevent survey bots.