传染的COVID-19模因:在面具背后的多种多式声音上
Marta Dynel1,2
1University of Łódź, Poland.
概括
这项研究分析了幽默的COVID-19面具模因,揭示了多式调音和回声如何塑造在线幽默. 模因重新使用或扭曲原始声音,强调用户生成内容的复杂性.
科学领域:
- 数字通信数字通信
- 社交媒体分析 社交媒体分析
- 语言学的语言学.
背景情况:
- 用户生成的内容,特别是meme,是网络沟通和幽默的重要形式.
- COVID-19面具meme为分析数字环境中的多式联络表达提供了一个丰富的案例研究.
- 现有的关于meme的研究往往忽视了多模式表达和文本间的复杂性.
研究的目的:
- 推进多式发声的概念,用于分析用户生成的在线幽默.
- 为了调查流行社交媒体平台上的幽默的COVID-19口罩模因.
- 探索嵌套的声音如何有助于记忆的趋势和意义的创造.
主要方法:
- 来自四个社交媒体平台的meme corpus的多模式话语分析.
- 识别和检查主导的记忆力趋势及其依赖于嵌套的声音.
- 分析兼容和分离的多模态声音,包括分离性回声和 parodic 回声.
主要成果:
- 有趣的COVID-19面具模因主要利用嵌套的多式联络声音.
- 记忆学趋势依赖于兼容或分离的声音,例如反响个体或集体声音.
- 模因的重新发布和病毒传播导致了原始声音的重新利用或扭曲.
结论:
- 多模态表达,文本间和回声是模因研究的有价值的分析工具.
- 这项研究揭示了认识论上的模两可在理解meme背后的声音方面.
- 这项研究为数字幽默和在线通信提供了新的理论和方法见解.
关键词:
这里是回声回声 (Echo Echo).认识论上的模两可互文本性 互文本性一个MEME一个MEME一个MEME多模式幽默 在线幽默一个模仿,一个刺.参与者角色 参与者角色有趣的玩 trolling 在这里.病毒性 病毒性一个声音,一个声音,一个声音.更多相关视频
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