情感拓:使用词嵌入从文本中提取情感的基本组成部分
Hubert Plisiecki1, Adam Sobieszek2
1Research Lab for the Digital Social Sciences, IFIS PAN, Warsaw, Poland.
Frontiers in psychology
|October 23, 2024
概括
词嵌入,一种新的文本分析方法,成功地在社交媒体数据中识别了情感组件. 这种数据驱动的方法反映了语言中情绪的维度结构,为心理现象提供了新的见解.
科学领域:
- 计算语言学 计算语言学
- 心理学 心理学 心理学
- 自然语言处理自然语言处理.
背景情况:
- 传统的情感分析通常依赖于预先定义的理论框架.
- 从自然语言中理解情绪的维度结构是复杂的.
- 自动化方法为客观和数据驱动的心理学研究提供了潜力.
研究的目的:
- 探索词语嵌入作为一种用于情感分解分析的新方法.
- 使用文本数据直接从人类语言中提取情感维度.
- 调查文本的语义结构是否反映了情感的维度结构.
主要方法:
- 利用词嵌入来创建文本的数值表示.
- 从大型社交媒体数据集中构建了情绪向量.
- 对现有文献分析提取的情感成分.
主要成果:
- 词嵌入成功地识别了与已确定的发现相比的情绪组件.
- 该研究表明,文本表达式的语义结构反映了情感的维度结构.
- 这种方法提供了一个不受理论前提约束的替代视角.
结论:
- 词嵌入是分析人类情绪细微差别的一个有希望的工具.
- 这种方法在其他心理学领域也有潜在的应用.
- 这种数据驱动的方法增强了情感研究的生态有效性.
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