Correlates of Algorithmic News Exposure

• In Event: ICA Interactive Paper/Poster Session III
  In Interactive Poster Session: Communication and Technology Interactive Poster Session

Abstract

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.

Authors

• Patrick Weber, U of Hohenheim

• Fabian Prochazka, U of Hohenheim

• Lara Brueckner, University of Hohenheim

• Wolfgang Schweiger, U of Hohenheim