Supporting Credibility Assessment of News in Social Media using Star Ratings and Alternate Sources

Michael Kenning, Ryan Kelly, Simon Jones

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

This paper reports findings from a preliminary experiment in which we designed and tested two interface augmentations for enhancing credibility judgments of news stories on Facebook. We find that users’ credibility judgments can be improved by the two augmentations, though the changes in credibility scores were not statistically significant. However, participants spent longer using the design that gave them control over the evaluation process, and they appeared to be more confident about their choices when using it—despite the fact that their judgments were actually less accurate. We outline directions for future work based on these findings.
Original languageEnglish
Title of host publicationCHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
Pages1-6
Number of pages6
ISBN (Print)978-1-4503-5621-3
DOIs
Publication statusPublished - 21 Apr 2018

Fingerprint

News
Rating
Credibility
Social media
Augmentation
Evaluation
Facebook
Experiment

Keywords

  • Credibility Assessment
  • News Articles
  • Social Media

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

Cite this

Kenning, M., Kelly, R., & Jones, S. (2018). Supporting Credibility Assessment of News in Social Media using Star Ratings and Alternate Sources. In CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (pp. 1-6). [LBW592] Association for Computing Machinery. https://doi.org/10.1145/3170427.3188489

Supporting Credibility Assessment of News in Social Media using Star Ratings and Alternate Sources. / Kenning, Michael; Kelly, Ryan; Jones, Simon.

CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2018. p. 1-6 LBW592.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kenning, M, Kelly, R & Jones, S 2018, Supporting Credibility Assessment of News in Social Media using Star Ratings and Alternate Sources. in CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems., LBW592, Association for Computing Machinery, pp. 1-6. https://doi.org/10.1145/3170427.3188489
Kenning M, Kelly R, Jones S. Supporting Credibility Assessment of News in Social Media using Star Ratings and Alternate Sources. In CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. 2018. p. 1-6. LBW592 https://doi.org/10.1145/3170427.3188489
Kenning, Michael ; Kelly, Ryan ; Jones, Simon. / Supporting Credibility Assessment of News in Social Media using Star Ratings and Alternate Sources. CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2018. pp. 1-6
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