News cues: Information scent and cognitive heuristics

S. Shyam Sundar, Silvia Knobloch-Westerwick, Matthias R. Hastall

Research output: Contribution to journalArticlepeer-review

228 Scopus citations

Abstract

Google News and other newsbots have automated the process of news selection, providing Internet users with a virtually limitless array of news and public information dynamically culled from thousands of news organizations all over the world. In order to help users cope with the resultant overload of information, news leads are typically accompanied by three cues: (a) the name of the primary source from which the headline and lead were borrowed, (b) the time elapsed since the story broke, and (c) the number of related articles written about this story by other news organizations tracked by the newsbot. This article investigates the psychological significance of these cues by positing that the information scent transmitted by each cue triggers a distinct heuristic (mental shortcut) that tends to influence online users' perceptions of a given news item, with implications for their assessment of the item's relevance to their information needs and interests. A large 2×3×6 within-subjects online experiment (N = 523) systematically varied two levels of the source credibility cue, three levels of the upload recency cue and six levels of trie number-of-related-articles cue in an effort to investigate their effects upon perceived message credibility, newsworthiness, and likelihood of clicking on the news lead. Results showed evidence for source primacy effect, and some indication of a cue-cumulation effect when source credibility is low. Findings are discussed in the context of machine and bandwagon heuristics.

Original languageEnglish (US)
Pages (from-to)366-378
Number of pages13
JournalJournal of the American Society for Information Science and Technology
Volume58
Issue number3
DOIs
StatePublished - Mar 2007

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Networks and Communications
  • Artificial Intelligence

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