Man vs. Machine? The impact of algorithm authorship on news credibility

Facing budget constraints, many traditional news organizations are turning their eyes on automation to streamline manpower, cut down on costs, and improve efficiency. But how does automation fit into traditional values of journalism and how does it affect perceptions of credibility, an important cur...

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Main Authors: Tandoc, Edson C., Yao, Lim Jia, Wu, Shangyuan
Other Authors: Wee Kim Wee School of Communication and Information
Format: Article
Language:English
Published: 2022
Subjects:
Online Access:https://hdl.handle.net/10356/154737
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1547372022-01-05T08:30:47Z Man vs. Machine? The impact of algorithm authorship on news credibility Tandoc, Edson C. Yao, Lim Jia Wu, Shangyuan Wee Kim Wee School of Communication and Information Social sciences::Communication Automation Journalism Facing budget constraints, many traditional news organizations are turning their eyes on automation to streamline manpower, cut down on costs, and improve efficiency. But how does automation fit into traditional values of journalism and how does it affect perceptions of credibility, an important currency valued by the journalistic field? This study explores this question using a 3 (declared author: human vs. machine vs. combined) × 2 (objectivity: objective vs. not objective) between-subjects experimental design involving 420 participants drawn from the national population of Singapore. The analysis found no main differences in perceived source credibility between algorithm, human, and mixed authors. Similarly, news articles attributed to an algorithm, a human journalist, and a combination of both showed no differences in message credibility. However, the study found an interaction effect between type of declared author and news objectivity. When the article is presented to be written by a human journalist, source and message credibility remain stable regardless of whether the article was objective or not objective. However, when the article is presented to be written by an algorithm, source and message credibility are higher when the article is objective than when the article is not objective. Findings for combined authorship are split: there were no differences between objective and non-objective articles when it comes to message credibility. However, combined authorship is rated higher in source credibility when the article is not objective than when the article is objective. Ministry of Education (MOE) This research is supported by the corresponding author’s Tier 1 Grant (T1-002-125-05) awarded by the Singapore’s Ministry of Education. 2022-01-05T08:30:47Z 2022-01-05T08:30:47Z 2020 Journal Article Tandoc, E. C., Yao, L. J. & Wu, S. (2020). Man vs. Machine? The impact of algorithm authorship on news credibility. Digital Journalism, 8(4), 548-562. https://dx.doi.org/10.1080/21670811.2020.1762102 2167-0811 https://hdl.handle.net/10356/154737 10.1080/21670811.2020.1762102 2-s2.0-85086174313 4 8 548 562 en T1-002-125-05 Digital Journalism © 2020 Informa UK Limited, trading as Taylor & Francis Group. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Social sciences::Communication
Automation
Journalism
spellingShingle Social sciences::Communication
Automation
Journalism
Tandoc, Edson C.
Yao, Lim Jia
Wu, Shangyuan
Man vs. Machine? The impact of algorithm authorship on news credibility
description Facing budget constraints, many traditional news organizations are turning their eyes on automation to streamline manpower, cut down on costs, and improve efficiency. But how does automation fit into traditional values of journalism and how does it affect perceptions of credibility, an important currency valued by the journalistic field? This study explores this question using a 3 (declared author: human vs. machine vs. combined) × 2 (objectivity: objective vs. not objective) between-subjects experimental design involving 420 participants drawn from the national population of Singapore. The analysis found no main differences in perceived source credibility between algorithm, human, and mixed authors. Similarly, news articles attributed to an algorithm, a human journalist, and a combination of both showed no differences in message credibility. However, the study found an interaction effect between type of declared author and news objectivity. When the article is presented to be written by a human journalist, source and message credibility remain stable regardless of whether the article was objective or not objective. However, when the article is presented to be written by an algorithm, source and message credibility are higher when the article is objective than when the article is not objective. Findings for combined authorship are split: there were no differences between objective and non-objective articles when it comes to message credibility. However, combined authorship is rated higher in source credibility when the article is not objective than when the article is objective.
author2 Wee Kim Wee School of Communication and Information
author_facet Wee Kim Wee School of Communication and Information
Tandoc, Edson C.
Yao, Lim Jia
Wu, Shangyuan
format Article
author Tandoc, Edson C.
Yao, Lim Jia
Wu, Shangyuan
author_sort Tandoc, Edson C.
title Man vs. Machine? The impact of algorithm authorship on news credibility
title_short Man vs. Machine? The impact of algorithm authorship on news credibility
title_full Man vs. Machine? The impact of algorithm authorship on news credibility
title_fullStr Man vs. Machine? The impact of algorithm authorship on news credibility
title_full_unstemmed Man vs. Machine? The impact of algorithm authorship on news credibility
title_sort man vs. machine? the impact of algorithm authorship on news credibility
publishDate 2022
url https://hdl.handle.net/10356/154737
_version_ 1722355353756106752