Users' ability to perceive misinformation: An information quality assessment approach. Issue 1 (January 2022)
- Record Type:
- Journal Article
- Title:
- Users' ability to perceive misinformation: An information quality assessment approach. Issue 1 (January 2022)
- Main Title:
- Users' ability to perceive misinformation: An information quality assessment approach
- Authors:
- Zrnec, Aljaž
Poženel, Marko
Lavbič, Dejan - Abstract:
- Abstract: Digital information exchange enables quick creation and sharing of information and thus changes existing habits. Social media is becoming the main source of news for end-users replacing traditional media. This also enables the proliferation of fake news, which misinforms readers and is used to serve the interests of the creators. As a result, automated fake news detection systems are attracting attention. However, automatic fake news detection presents a major challenge; content evaluation is increasingly becoming the responsibility of the end-user. Thus, in the present study we used information quality (IQ) as an instrument to investigate how users can detect fake news. Specifically, we examined how users perceive fake news in the form of shorter paragraphs on individual IQ dimensions. We also investigated which user characteristics might affect fake news detection. We performed an empirical study with 1123 users, who evaluated randomly generated stories with statements of various level of correctness by individual IQ dimensions. The results reveal that IQ can be used as a tool for fake news detection. Our findings show that (1) domain knowledge has a positive impact on fake news detection; (2) education in combination with domain knowledge improves fake news detection; and (3) personality trait conscientiousness contributes significantly to fake news detection in all dimensions. Highlights: IQ proved to be a successful instrument when applied to fake newsAbstract: Digital information exchange enables quick creation and sharing of information and thus changes existing habits. Social media is becoming the main source of news for end-users replacing traditional media. This also enables the proliferation of fake news, which misinforms readers and is used to serve the interests of the creators. As a result, automated fake news detection systems are attracting attention. However, automatic fake news detection presents a major challenge; content evaluation is increasingly becoming the responsibility of the end-user. Thus, in the present study we used information quality (IQ) as an instrument to investigate how users can detect fake news. Specifically, we examined how users perceive fake news in the form of shorter paragraphs on individual IQ dimensions. We also investigated which user characteristics might affect fake news detection. We performed an empirical study with 1123 users, who evaluated randomly generated stories with statements of various level of correctness by individual IQ dimensions. The results reveal that IQ can be used as a tool for fake news detection. Our findings show that (1) domain knowledge has a positive impact on fake news detection; (2) education in combination with domain knowledge improves fake news detection; and (3) personality trait conscientiousness contributes significantly to fake news detection in all dimensions. Highlights: IQ proved to be a successful instrument when applied to fake news identification. Foreknowledge and education have a positive impact on the recognition of fake news. Conscientious users are more successful in detecting fake news in all IQ dimensions. Neuroticism and extraversion impact selected IQ dimensions. … (more)
- Is Part Of:
- Information processing & management. Volume 59:Issue 1(2022)
- Journal:
- Information processing & management
- Issue:
- Volume 59:Issue 1(2022)
- Issue Display:
- Volume 59, Issue 1 (2022)
- Year:
- 2022
- Volume:
- 59
- Issue:
- 1
- Issue Sort Value:
- 2022-0059-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-01
- Subjects:
- Fake news -- Misinformation -- Information quality -- Big Five personality traits -- Fake news detection -- Case study
Information storage and retrieval systems -- Periodicals
Information science -- Periodicals
Systèmes d'information -- Périodiques
Sciences de l'information -- Périodiques
Information science
Information storage and retrieval systems
Periodicals
658.4038 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03064573 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ipm.2021.102739 ↗
- Languages:
- English
- ISSNs:
- 0306-4573
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4493.893000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19853.xml