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Serendipity by Design? How to Turn from Diversity Exposure to Diversity Experience to Face Filter Bubbles in Social Media

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Abstract

Personalization of online content creates filter bubbles and reinforces echo chambers. These are driven not only by natural human behaviours but also by design choices and efficiency-driven recommender systems. The traditional media policy goal of exposing citizens to diverse information to protect pluralism has not found its concrete application on social media. As the usage of social media as a news source increases, as well as personalization’ sophistication and group polarization, there is a need for preventing audience fragmentation. The paper suggests serendipity as a potential design principle and, eventually, policy goal. Indeed, serendipity – considered both as a capability and a process of seeking and processing unexpected and valuable information – requires diverse information as a precondition and it causes cognitive diversity. Serendipity as a design principle might encompass fundamental phases of production and consumption of information, representing a positive freedom valuable from an epistemological, psychological and political perspective. With serendipity being both limited and cultivated in the digital environment, the research reveals a theoretical trade-off between relevance and serendipity (or unknown relevance) that might be tackled with serendipity-driven recommender systems and structural and informational nudging. Such approach could turn the media policy goal of exposing users to diverse information towards an experience of diversity that comes through an architecture for serendipity.

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This research is funded by the ERASMUS MUNDUS program LAST-JD, Law, Science and Technology coordinated by University of Bologna.

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Correspondence to Urbano Reviglio .

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Reviglio, U. (2017). Serendipity by Design? How to Turn from Diversity Exposure to Diversity Experience to Face Filter Bubbles in Social Media. In: Kompatsiaris, I., et al. Internet Science. INSCI 2017. Lecture Notes in Computer Science(), vol 10673. Springer, Cham. https://doi.org/10.1007/978-3-319-70284-1_22

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