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Using machine learning to learn machines: a cross-cultural study of users’ responses to machine-generated artworks


Xu, Kun; Liu, Fanjue; Mou, Yi; Wu, Yuheng; Zeng, Jing; Schäfer, Mike S (2020). Using machine learning to learn machines: a cross-cultural study of users’ responses to machine-generated artworks. Journal of Broadcasting and Electronic Media, 64(4):566-591.

Abstract

Drawing upon prior literature on machine-generated news, this study expands the research scope to machine-generated art works in a cross-cultural context. This study combines machine learning approaches with online experiments and investigates how different genres of art works and different authorship cues influence participants’ open-ended responses to machine-generated works. Results suggest that while genres and cultures affected participants’ discussion topics and word use, the differences between participants’ responses to machine-generated art works and human-generated ones were not evident. This study tests the explanatory power of machine heuristic and demonstrates the feasibility of integrating multiple methods in future AI-based media research.

Abstract

Drawing upon prior literature on machine-generated news, this study expands the research scope to machine-generated art works in a cross-cultural context. This study combines machine learning approaches with online experiments and investigates how different genres of art works and different authorship cues influence participants’ open-ended responses to machine-generated works. Results suggest that while genres and cultures affected participants’ discussion topics and word use, the differences between participants’ responses to machine-generated art works and human-generated ones were not evident. This study tests the explanatory power of machine heuristic and demonstrates the feasibility of integrating multiple methods in future AI-based media research.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Department of Communication and Media Research
Dewey Decimal Classification:700 Arts
Scopus Subject Areas:Social Sciences & Humanities > Communication
Uncontrolled Keywords:Cross-cultural comparisons, machine heuristic, AI-generated content, machine agency, automated text analysis, artificial intelligence
Language:English
Date:9 December 2020
Deposited On:11 Feb 2021 07:30
Last Modified:30 Apr 2021 07:17
Publisher:Taylor & Francis
ISSN:0883-8151
OA Status:Closed
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1080/08838151.2020.1835136

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Language: English
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Embargo till: 2022-06-09