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Diving Into the Rabbit Hole: Understanding Delegation of Decisions

Diving Into the Rabbit Hole: Understanding Delegation of Decisions
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Author(s): Mateus Coimbra (Universidade Federal do Rio de Janeiro, Brazil), Paula Chimenti (Universidade Federal do Rio de Janeiro, Brazil)and Roberto Nogueira (Universidade Federal do Rio de Janeiro, Brazil)
Copyright: 2023
Pages: 15
Source title: Encyclopedia of Data Science and Machine Learning
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-7998-9220-5.ch014

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Abstract

Experts highlight their concern about the excessive use of social media, with people systematically declaring to enter social networks for a specific purpose and leaving hours after diving into the “rabbit hole.” This overuse has been associated with the ability of platform recommendation algorithms to assign content of interest. The combination of machine learning algorithms with big data evolves the predictive power of these recommendation systems, leading to new perspectives for people to interact with the platforms. This article studied human-machine interaction mechanisms and motivators of this process. The authors integrated different perspectives found in the literature into a comprehensive model which tries to explain which factors would help to understand this mechanism of interaction. A survey was carried out with 297 YouTube users. The model presented different findings as the presence of two paths of interaction with different motivators. Escapism is a motivator for both routes. Both routes had impacts in terms of satisfaction and dependence, with exchanged forces.

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