Analyzing users’ trust for online health rumors

Alton Y.K. Chua*

*Corresponding author for this work

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

21 Citations (Scopus)

Abstract

This paper analyzes users’ trust for online health rumors as a function of two factors: length and presence of image. Additionally, two types of rumors are studied: pipe-dream rumors that offer hope, and bogie rumors that instil fear. A total of 102 participants took part in a 2 (length: short or long) x 2 (presence of image: absent or present) x 2 (type: pipe-dream or bogie) within-participants experiment. A repeated-measures analysis of variance suggest that pipe-dream rumors are trusted when they are short and do not contain images whereas bogie rumors are trusted when they are long and contain images.

Original languageEnglish
Title of host publicationDigital Libraries
Subtitle of host publicationProviding Quality Information - 17th International Conference on Asia-Pacific Digital Libraries, ICADL 2015, Proceedings
EditorsRobert B. Allen, Jane Hunter, Marcia L. Zeng
PublisherSpringer Verlag
Pages33-38
Number of pages6
ISBN (Print)9783319279732
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event17th International Conference on Digital Libraries: Providing Quality Information, ICADL 2015 - Seoul, Korea, Republic of
Duration: Dec 9 2015Dec 12 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9469
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Digital Libraries: Providing Quality Information, ICADL 2015
Country/TerritoryKorea, Republic of
CitySeoul
Period12/9/1512/12/15

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

ASJC Scopus Subject Areas

  • Theoretical Computer Science
  • General Computer Science

Keywords

  • Online health information
  • Rumor
  • Trust
  • Virality

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