Yazici, Edanur; Wang, Ying; (2023) Attack the bot: Mode effects and the challenges of conducting a mixed-mode household survey during the Covid-19 pandemic. International Journal of Social Research Methodology 10.1080/13645579.2023.2241797. (In press).

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Abstract

Constant changes to COVID-19 restrictions have required adaptability from social scientists including responding to new challenges such as infiltration by bots. This research note presents unexpected encounters of bot infiltration and recruitment during survey data collection under pandemic conditions. The note draws from a household survey on a social housing estate in London, UK conducted in 2021. The survey investigates residents’ lived experiences of the estate and housing turnover. The note discusses the limitations of online data collection, focusing on infiltration by bots and exclusion of marginalised groups. It adds to the emerging literature on bots in survey methods, making recommendations for an iterative verification and sequential multi-stage data cleaning process. It finds that online-only approaches can exclude marginalised groups. The note argues that even under pandemic conditions, face-to-face data collection can have greater reach than online only approaches. It concludes that mixed-mode household surveys can a) mitigate the challenges of a changing research environment; b) reach a broader sample; and c) provide qualitative insight for future research.

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