"算法会把你搞":指责,社会行为者和2020年A级结果算法在Twitter上
Dan Heaton1, Elena Nichele1,2, Jeremie Clos1
1School of Computer Science, University of Nottingham, Nottingham, Nottinghamshire, United Kingdom.
PloS one
|July 26, 2023
概括
2020年A级算法丑闻的责任归咎于该算法,英国政府和Ofqual. 语料库语言学和批判性话语分析揭示了微妙的社会行为者的代表性,与学生分配有限的责任.
科学领域:
- 计算语言学 计算语言学
- 社会科学 社会科学 社会科学
- 话语分析 话语分析
背景情况:
- 2020年8月,英国用算法取代了A级考试,后来在公众的抗议之后转向教师成绩.
- 之前对Twitter话语的分析使用了基于NLP的意见挖掘,但面临着准确性和解释性的局限性.
- 2020年A级分级丑闻在社交媒体上产生了关于问责制的重大公共话语.
研究的目的:
- 分析有关2020年A级算法丑闻的Twitter话语中的责怪归因.
- 通过应用体语言学 (CL) 和批判性话语分析 (CDA) 来补充现有的NLP研究.
- 在围绕算法的话语中检查社会行为者的代表性和代理性.
主要方法:
- 分析了与2020年A级算法相关的18239条推文.
- 体语言学 (CL) 和批判性话语分析 (CDA) 方法的应用.
- 检查过渡性和社会参与者的代表性,以确定归咎.
主要成果:
- 算法,英国政府和Ofqual被认为是负责A级评分问题的社会行为者.
- 责怪是通过积极的代理,隐喻的占有和被动的构造来归因的.
- 学生们被发现在分析的演讲中对他们的指责有限.
结论:
- CL和CDA为NLP工具提供了有价值的补充方法,用于分析A级丑闻等复杂的社会话语.
- 话语中使用的各种语言构造有助于掩盖明确的指责归属.
- 进一步的研究可以探索CL和CDA的代应用,以深入了解公共话语.
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