Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/167527
Authors: 
Germano, Fabrizio
Sobbrio, Francesco
Year of Publication: 
2017
Series/Report no.: 
CESifo Working Paper 6541
Abstract: 
Ranking algorithms are the information gatekeepers of the Internet era. We develop a stylized framework to study the effects of ranking algorithms on opinion dynamics. We consider rankings that depend on popularity and on personalization. We find that popularity driven rankings can enhance asymptotic learning while personalized ones can both inhibit or enhance it, depending on whether individuals have common or private value preferences. We also find that ranking algorithms can contribute towards the diffusion of misinformation (e.g., “fake news”), since lower ex-ante accuracy of content of minority websites can actually increase their overall traffic share.
Subjects: 
search engines
ranking algorithm
search behavior
opinion dynamics
information aggregation
asymptotic learning
misinformation
polarization
website traffic
fake news
JEL: 
D83
L86
Document Type: 
Working Paper
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