How recommendation systems lead to polarization
Researchers: Prof. Sigal Alon )Sociology and Anthropology), Prof. Dafna Gelbgiser (Labor Studies), Prof. Ran Gilad-Bachrach (Bio-medical engineering)
Researchers: Prof. Sigal Alon )Sociology and Anthropology), Prof. Dafna Gelbgiser (Labor Studies), Prof. Ran Gilad-Bachrach (Bio-medical engineering)
Social Networking Sites (SNSs) have become the new town hall. We get much of our news through SNSs, and this is where we hold discussions and debates. Therefore, SNSs have large influence on opinions and decisions.
At the heart of these SNSs there are recommendation systems that tailor the feed to our preferences. These systems use machine learning algorithms to make the feed more to our liking.
Therefore, these machine learning algorithms shape the way we perceive the world. The goal of this study is to answer the fundamental question: Do SNSs actively change people opinions or, alternatively, do the SNSs just reflect users’ opinions to them?
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