Publication Date:
2016
abstract:
Search engines and social media keep trace of profile- and behavioral-based distinct signals of their users, to provide them person- alized and recommended content. Here, we focus on the level of web search personalization, to estimate the risk of trapping the user into so called Filter Bubbles. Our experimentation has been carried out on news, specifically investigating the Google News platform. Our results are in line with existing literature and call for further analyses on which kind of users are the target of specific recommendations by Google.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Filter bubbles; web search results; news publishers
List of contributors: