Designing Artificial Serendipity

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Abstract

Designing for serendipity in online platforms has drawn considerable attention and debate over the last decade. To shed light on the debate and seek effective strategies for designing serendipity, a narrative inquiry was conducted with 32 Chinese online consumers. By learning from their experience of the designed serendipity (i.e. artificial serendipity) from real-life stories told via diary and interview, the findings revealed that artificial serendipity is a unique type of serendipity that provides platform users with constant surprises that can lead to both beneficial and harmful outcomes. Further, users appreciate artificial serendipity when it incorporates elements such as personalisation, controllability, and moderate propagation. These findings provide insights for research by expanding the current understanding of serendipity as an interplay between individual and random contexts, revealing that serendipity can also stem from a conscious designed context. For practice, these findings underscore that the design of artificial serendipity should focus more on platform users’ ideas while refining existing online platform designs.

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APA

Chen, X., Lin, A., & Webber, S. (2024). Designing Artificial Serendipity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 14684 LNCS, pp. 28–45). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-60405-8_3

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