Experimental Measures of News Personalization in Google News

Vittoria Cozza, Van Tien Hoang, Marinella Petrocchi, Angelo Spognardi

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Search engines and social media keep trace of profile- and behavioral-based distinct signals of their users, to provide them personalized 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.
Original languageEnglish
Title of host publicationCurrent Trends in Web Engineering : Revised Selected Papers from the ICWE 2016 International Workshops DUI, TELERISE, SoWeMine, and Liquid Web
PublisherSpringer
Publication date2016
Pages93-104
ISBN (Print)978-3-319-46962-1
ISBN (Electronic)978-3-319-46963-8
DOIs
Publication statusPublished - 2016
Event2nd International Workshop on TEchnical and LEgal aspects of data pRIvacy and SEcurity (TELERISE 2016): Affiliated workshop with ICWE 2016 - USI Lugano, Switzerland
Duration: 9 Jun 20169 Jun 2016
Conference number: 2
http://www.iit.cnr.it/telerise2016/

Conference

Conference2nd International Workshop on TEchnical and LEgal aspects of data pRIvacy and SEcurity (TELERISE 2016)
Number2
CountrySwitzerland
CityUSI Lugano
Period09/06/201609/06/2016
Internet address
SeriesLecture Notes in Computer Science
Volume9881
ISSN0302-9743

Keywords

  • Filter bubbles
  • Web search results
  • News publishers

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