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

Michael Kenning; Ryan Kelly; Simon Jones

doi:10.1145/3170427.3188489

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

Michael Kenning, Ryan Kelly, Simon Jones

Department of Computer Science

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

1 Citation (SciVal)

124 Downloads (Pure)

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 language	English
Title of host publication	CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
Publisher	Association for Computing Machinery
Pages	1-6
Number of pages	6
ISBN (Print)	978-1-4503-5621-3
DOIs	https://doi.org/10.1145/3170427.3188489
Publication status	Published - 21 Apr 2018

Keywords

Credibility Assessment
News Articles
Social Media

ASJC Scopus subject areas

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

Access to Document

10.1145/3170427.3188489

paper1163
(C) ACM, 2018. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CHI'18 Extended Abstracts, 21 - 26 April 2018, http://doi.acm.org/10.1145/3170427.3188489
Accepted author manuscript, 2.58 MBLicence: Unspecified

Cite this

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 or section in a book/report/conference proceeding › Chapter in a published conference proceeding

@inproceedings{24acb395f21540ff85ee7217f52ec077,

title = "Supporting Credibility Assessment of News in Social Media using Star Ratings and Alternate Sources",

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{\textquoteright} 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.",

keywords = "Credibility Assessment, News Articles, Social Media",

author = "Michael Kenning and Ryan Kelly and Simon Jones",

year = "2018",

month = apr,

day = "21",

doi = "10.1145/3170427.3188489",

language = "English",

isbn = "978-1-4503-5621-3",

pages = "1--6",

booktitle = "CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems",

publisher = "Association for Computing Machinery",

address = "USA United States",

}

TY - GEN

T1 - Supporting Credibility Assessment of News in Social Media using Star Ratings and Alternate Sources

AU - Kenning, Michael

AU - Kelly, Ryan

AU - Jones, Simon

PY - 2018/4/21

Y1 - 2018/4/21

N2 - 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.

AB - 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.

KW - Credibility Assessment

KW - News Articles

KW - Social Media

UR - http://www.scopus.com/inward/record.url?scp=85052022201&partnerID=8YFLogxK

U2 - 10.1145/3170427.3188489

DO - 10.1145/3170427.3188489

M3 - Chapter in a published conference proceeding

SN - 978-1-4503-5621-3

SP - 1

EP - 6

BT - CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems

PB - Association for Computing Machinery

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this