首页> 外文期刊>Journal of broadcasting & electronic media >Using Machine Learning to Learn Machines: A Cross-Cultural Study of Users' Responses to Machine-Generated Artworks
【24h】

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

机译:利用机器学习学习机器:用户对机器生成的作品的反应的跨文化研究

获取原文
获取原文并翻译 | 示例
           

摘要

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.
机译:从现有文学中绘制在机器生成的新闻上,本研究审查了在跨文化背景下的机器生成的艺术品。 它将机器学习方法与在线实验结合起来,并调查艺术品种类和不同作者提示的不同类型如何影响参与者对机器生成的作品的开放式反应。 结果表明,虽然流派和文化影响了参与者的讨论主题和词汇,但参与者对机器生成的作品和人生成的答复之间的差异并不明显。 本研究测试了机器启发式的解释性,并展示了在未来的基于AI的媒体研究中集成了多种方法的可行性。

著录项

  • 来源
    《Journal of broadcasting & electronic media》 |2020年第4期|566-591|共26页
  • 作者单位

    Univ Florida Coll Journalism & Commun Gainesville FL 32611 USA;

    Univ Florida Coll Journalism & Commun Gainesville FL 32611 USA;

    Shanghai Jiao Tong Univ Sch Media & Commun Shanghai Peoples R China;

    Shanghai Jiao Tong Univ Sch Media & Commun Shanghai Peoples R China;

    Univ Zurich Dept Commun & Media Res Zurich Switzerland;

    Univ Zurich Dept Commun & Media Res Zurich Switzerland;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号