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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Although black holes were theoretically postulated in the 1920s, they remained outside the domain of observational astronomy until the 1970s.
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Lesson: Translation
Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
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Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
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跨语言的仇恨言论检测使用特定域名的词嵌入.

Ayme Arango Monnar1, Jorge Perez Rojas2, Barbara Polete Labra1,3

  • 1Computer Science Department, Universidad de Chile, Santiago de Chile, Chile.

PloS one
|July 30, 2024
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概括

这项研究引入了一种新的多语言嵌入模型来检测仇恨言论,在零射击跨语言场景中表现优于现有模型. 这项研究突出了网上仇恨言论表达中常见的跨语言模式.

科学领域:

  • 自然语言处理 (NLP) 是一种自然语言处理.
  • 计算语言学 计算语言学
  • 社交网络分析 社交网络分析

背景情况:

  • 由于语言和文化细微差别,检测仇恨言论具有挑战性.
  • 现有的NLP工具主要以英语为中心,限制了多语言应用.
  • 为了检测仇恨言论,有效的跨语言传输仍然是一个未得到满足的需求.

研究的目的:

  • 开发一种高效的多语言仇恨言论检测方法.
  • 创建第一个专门用于仇恨言论检测的多语言嵌入模型.
  • 为了提高检测,利用有限的跨语言资源.

主要方法:

  • 为仇恨言论开发一个专门的多语言嵌入模型.
  • 与通用语言模型进行广泛的比较评估.
  • 在仇恨言论分类任务中进行零射击跨语言评估.

主要成果:

  • 建议的专业嵌入在大多数测试设置中表现优于复杂的通用模型.
  • 该模型在没有先前标记数据的情况下,在跨语言的仇恨言论分类方面表现出有效性.
  • 定性分析揭示了仇恨言论术语中的新的跨语言关系.

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结论:

  • 开发的多语言嵌入模型是有效的跨语言仇恨言论检测.
  • 在不同语言中如何表达仇恨言论存在共同的模式.
  • 该模型成功地捕捉了这些跨语言关系,提供了显著的进步.