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Audiences increasingly use algorithmically personalized media such as social network sites, search engines or news apps for information about current affairs. This raises the concern that recipients receive like-minded information instead of a broad and comprehensive overview of current events. However, there are limited studies available concerning the actual amount of algorithmically personalized media people use and who uses them. We conducted a representative online survey in Germany to measure a) the (absolute and relative) exposure to algorithmic news based on a new typology of sources and b) user characteristics associated with algorithmic news use. The share of algorithmically personalized sources in total news use is on average 25% (SD = 27%), which indicates a relatively high importance of these sources. Results of a multiple regression model show various factors associated with algorithmic news use, such as demographics, personality traits and general tendencies of media use.
Patrick Weber, U of Hohenheim
Fabian Prochazka, U of Hohenheim
Lara Brueckner, University of Hohenheim
Wolfgang Schweiger, U of Hohenheim