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Using Explanations as Energy-Saving Frames: A User-Centric Recommender Study

, , and . Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, page 229-237. ACM, (June 2021)
DOI: 10.1145/3450614.3464477

Abstract

Recommender systems usually seek to cater to the preferences of a single user. However, societal issues that involve multiple stakeholders, such as climate change, cannot be mitigated this way. We address this issue by going beyond traditional algorithms, using psychological theories to not only optimize what is recommended (i.e., the algorithm), but also how interface items are presented. We present the ‘Saving Aid’ recommender system for household energy conservation, encouraging users to adopt energy-saving measures with high kWh savings, such as buying environmentally-friendly electronic appliances. In an online user study (N = 258), we compare different interfaces that promote measures with high kWh savings using different framing techniques, presenting either a kWh savings score or a Smart Savings Score that combines effort and kWh savings. We show that framing positively affects the extent to which users consider kWh savings when choosing a measure, without compromising the user’s system evaluation.

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Using Explanations as Energy-Saving Frames: A User-Centric Recommender Study | Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization

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