Experimental measures of news personalization in Google News
| Autor: | Angelo Spognardi, Marinella Petrocchi, Vittoria Cozza, Van Tien Hoang |
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| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Focus (computing)
Computer science Web search results 05 social sciences Computer Science (all) 050801 communication & media studies computer.software_genre Filter (software) News aggregator Personalization Theoretical Computer Science World Wide Web 0508 media and communications Filter bubbles Social media 0509 other social sciences 050904 information & library sciences computer News publishers TRACE (psycholinguistics) |
| Zdroj: | Current Trends in Web Engineering ISBN: 9783319469621 ICWE Workshops |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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