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Paper Number

2341

Paper Type

short

Description

Personalized news platforms (PNPs) have become increasingly popular due to their ability to provide users with tailored, relevant news content. However, their algorithmic selection of news items bears the risk of limiting the diversity of news that users are exposed to, potentially creating information-limiting environments (ILEs). As the emergence of such ILEs involves interdependent sociotechnical interactions, classical positivist approaches have failed to establish an empirically verified theory on this phenomenon. Therefore, we adopt a systems perspective to conceptualize and quantify a model describing the sociotechnical interactions in PNPs that can create ILEs. We then propose an experimental approach to simulate these interactions with real users and validate its viability through an empirical prestudy. In doing so, we contribute to IS research by providing the conceptual and methodological basis for inductive theorizing on the causes of ILEs, which is an essential prerequisite for designing effective interventions to mitigate ILE-induced risks.

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Dec 11th, 12:00 AM

Understanding Information-Limiting Environments in Personalized News Platforms—A Systems Perspective

Personalized news platforms (PNPs) have become increasingly popular due to their ability to provide users with tailored, relevant news content. However, their algorithmic selection of news items bears the risk of limiting the diversity of news that users are exposed to, potentially creating information-limiting environments (ILEs). As the emergence of such ILEs involves interdependent sociotechnical interactions, classical positivist approaches have failed to establish an empirically verified theory on this phenomenon. Therefore, we adopt a systems perspective to conceptualize and quantify a model describing the sociotechnical interactions in PNPs that can create ILEs. We then propose an experimental approach to simulate these interactions with real users and validate its viability through an empirical prestudy. In doing so, we contribute to IS research by providing the conceptual and methodological basis for inductive theorizing on the causes of ILEs, which is an essential prerequisite for designing effective interventions to mitigate ILE-induced risks.

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