Abstract
Despite the various advantages of online surveys, such as their cost-effectiveness and broad reach, the infiltration of bots can result in data distortion, eroding trust and hindering effective decision-making. Identifying bot responses within survey data is paramount, and epidemiologic and public health researchers can utilise various tactics such as email authentication and scrutiny of response times, to detect fraudulent responses. This paper discusses the authors' experience of bot spamming in an online survey, which skewed our findings. We discuss the actions taken to detect and invalidate bot responses within survey data and discuss potential forms of bot prevention. To detect fraudulent responses, the authors investigated the time taken to complete the survey, recruitment rates, invalid email addresses, and invalid free-format responses. Supplementary strategies, such as data validation methods and monitoring tools, can complement reCAPTCHA systems to alleviate the adverse effects of bot activity on survey data accuracy. However, employing other methods that require challenges, or additional questions may reduce the recruitment rate and deter potential participants. Given the advancing sophistication of bots, ongoing innovation in authentication techniques is imperative to protect the dependability and accuracy of survey data in the future.
Original language | English |
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Article number | 20240026 |
Journal | Epidemiologic Methods |
Volume | 14 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jan 2025 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2025 the author(s), published by De Gruyter, Berlin/Boston.
Keywords
- bot detection algorithms
- bots
- data integrity
- data quality
- spam
- survey methodology