Framing Effects and Algorithm-Based News Recommendation Systems

• In Event: ICA Interactive Paper/Poster Session II
  In Interactive Poster Session: Political Communication Interactive Poster Session

Abstract

Online news organizations use a keyword-based news recommendation system to suggest additional news stories to readers. However, past news framing experiments have ignored the “recommended news for you” section that displays headlines of related news stories. Thus, this study investigates the framing effects of online editorials and their accompanying recommended headlines. A 5×2 (5 editorial frames × presence vs. absence of recommended headlines) online experiment was conducted with adult participants. Results suggest that recommended headlines that share the same frame with the editorial made the respondents perceive the editorial as more credible and influential generally. However, regarding issue-related attitudes and emotions, the additional headlines reinforced the effects of the editorial when the frame’s relevance to the readers was high, but undermined the editorial’s impact when the relevance was low. Implications for future framing studies and online news consumption are discussed.

Authors

• Jiawei Liu, U of Wisconsin-Madison

• ByungGu Lee, U of Wisconsin-Madison

• Douglas M. McLeod, U of Wisconsin-Madison

• Hyesun Choung