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Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
Abstract
Searching for people online is a common search task that most of us have performed at some point or other. With so much information about people available online it is often amazing what one can find out about someone else – especially when information taken from different sources is pieced together to create a more detailed picture of the individual, and then used to make inferences about them (leading to cumulative revelations). As such, the relevance of one piece of information is often conditional and dependent on other pieces of information found. This creates interesting and novel challenges in evaluating information relevance when searching personal profiles, posts and related information about an individual, as well as the potential risks that can arise from such revelations. In this demonstration paper, we present a tool designed to investigate how people assess and judge the relevance and potential risks of small, apparently innocuous pieces of information associated with fictitious personas, such as Taylor Addison, when searching and browsing online profiles and social media. The demonstrator also comprises a cyber-safety tool, which aims to provide education and raise awareness of the potential risks of cumulative revelations. It does so by engaging participants in different scenarios where the relevance of individual information items depends on the searcher and their particular underlying motivation.
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Cited by
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From Matching to Generation: A Survey on Generative Information Retrieval
Li, X., Jin, J., Zhou, Y., Zhang, Y., Zhang, P., Zhu, Y., & Dou, Z. (2025) · ACM Transactions on Information Systems · doi:10.1145/3722552 · Cited by 172
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Hauptman, A. I., Schelble, B. G., McNeese, N. J., & Madathil, K. C. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107451 · Cited by 110
Wang, F., Zhang, Z., Zhang, X., Wu, Z., Mo, T., Lu, Q., Wang, W., Li, R., Xu, J., Tang, X., et al. (2025) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3768165 · Cited by 106
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Metadata
- Publisher
- ACM
- Published
- 2022-07-06
- OpenAlex
- W2069065514
- Cited by
- 907
- References
- 0
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- Language
- en
- Open access
- closed
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