PUMA
Istituto di Informatica e Telematica     
Petrocchi M., Cozza V., Spognardi A., Hoang V. T. Experimental measures of news personalization in Google News. In: ICWE 2016 - ICWE 2016 International Workshops, DUI, TELERISE, SoWeMine, and Liquid Web (Lugano, Switzerland, 06-06 2016). Proceedings, vol. 9881 pp. 93 - 104. Sven Casteleyn, Peter Dolog, Cesare Pautasso (eds.). (Lecture Notes in Computer Science). Springer, 2016.
 
 
Abstract
(English)
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.
URL: http://link.springer.com/chapter/10.1007/978-3-319-46963-8_8
DOI: 10.1007/978-3-319-46963-8_8
Subject news publishers
web search results
Filter Bubbles
H.2.8 Database Applications Data mining


Icona documento 1) Download Document PDF


Icona documento Open access Icona documento Restricted Icona documento Private

 


Per ulteriori informazioni, contattare: Librarian http://puma.isti.cnr.it

Valid HTML 4.0 Transitional