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企业沟通跨语言分析的同等情绪指标

Karol Marek Klimczak¹, Jan Makary Fryczak¹, Dominika Hadro²

¹Institute of Management, Faculty of Organization and Management, Lodz University of Technology, Wólczańska 221, 93-005, Łódź, Poland.

|May 23, 2024

概括

本研究介绍了一种基于Python的方法,用于跨语言情绪分析,使得对多语言企业文件的高效研究成为可能. 该技术使用开放的多语言WordNet提取跨语言的可比情感特征.

科学领域:

计算语言学计算语言学
自然语言处理自然语言处理.
情绪分析情绪分析

背景情况:

在多语言的企业文件中分析情绪,由于语言多样性而存在挑战.
现有的情绪分析工具往往缺乏强大的跨语言能力.
全球财务和管理报告的定量分析需要有效的方法.

研究的目的:

开发和验证一种创新的技术,用于创建跨多种语言的等效情绪测量.
通过使用Python,使用各种语言对公司文件进行高效的情感分析.
促进跨语言统计分析和机器学习在商业研究中的应用.

主要方法:

利用开放的多语言WordNet,一个涵盖200多种语言的全面词典,作为核心知识库.
开发了一个基于Python的方法来从文本中提取等效的跨语言情感特征.
采用了平行英法语语库来经验验证情绪测量技术.

主要成果:

使用拟议的方法,在英语和法语中展示了可比的情绪指标.
在两种语言中实现了正面和负面文本的一致分类.
展示了两种语言之间的相关情绪测量值,表明了可靠性.

结论:

本技术提供了一种可靠的方法,用于在多种语言中生成同等的情绪指标.
这种基于已建立的词典和WordNet的方法在英语和法语中得到了验证,并适用于其他语言.
这有助于通过多语言情绪分析在文本挖掘,定量沟通研究和管理研究方面取得进展.

关键词:

商业沟通商业沟通财务报告财务报告在这里,Python是Python.文本挖掘 (Text Mining) 是一种文字挖掘方式.文本分析文本分析基于Wordnet的财务字典的翻译用于文本分析.

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