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Using Machine Learning to Learn Machines: A Cross-Cultural Study of Users' Responses to Machine-Generated Artworks.

Authors :
Xu, Kun
Liu, Fanjue
Mou, Yi
Wu, Yuheng
Zeng, Jing
Schäfer, Mike S.
Source :
Journal of Broadcasting & Electronic Media. Oct2020, Vol. 64 Issue 4, p566-591. 26p. 2 Black and White Photographs, 4 Charts, 5 Graphs.
Publication Year :
2020

Abstract

Drawing from prior literature on machine-generated news, this study examines machine-generated artworks in a cross-cultural context. It combines machine learning approaches with online experiments and investigates how different genres of artworks 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 artworks 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 FROM AUTHOR]

Details

Language :
English
ISSN :
08838151
Volume :
64
Issue :
4
Database :
Academic Search Index
Journal :
Journal of Broadcasting & Electronic Media
Publication Type :
Academic Journal
Accession number :
148772711
Full Text :
https://doi.org/10.1080/08838151.2020.1835136