论文标题
Kote用户指南：韩国在线评论情绪数据集
User Guide for KOTE: Korean Online Comments Emotions Dataset
论文作者
论文摘要
尽管对情感含义的彻底检查不足，但将数据分类为正或负面的情感分析已主要用于识别文本的情感方面。最近，构建了超过价值超过该限制的公司的标记的Corpora。但是，大多数韩国情感语料库在实例数量上很小，并且涵盖了有限的情绪。我们介绍Kote数据集。 Kote包含50k（250K案例）韩国在线评论，每个评论都用众包手动标记为43个情感标签或一个特殊标签（无情感）（PS = 3,048）。通过对单词嵌入空间表达的韩国情绪概念的群集分析，可以系统地确定43种情感的情感分类法。在解释了Kote的发展方式之后，我们还讨论了语料库中社会歧视的填充和分析结果。
Sentiment analysis that classifies data into positive or negative has been dominantly used to recognize emotional aspects of texts, despite the deficit of thorough examination of emotional meanings. Recently, corpora labeled with more than just valence are built to exceed this limit. However, most Korean emotion corpora are small in the number of instances and cover a limited range of emotions. We introduce KOTE dataset. KOTE contains 50k (250k cases) Korean online comments, each of which is manually labeled for 43 emotion labels or one special label (NO EMOTION) by crowdsourcing (Ps = 3,048). The emotion taxonomy of the 43 emotions is systematically established by cluster analysis of Korean emotion concepts expressed on word embedding space. After explaining how KOTE is developed, we also discuss the results of finetuning and analysis for social discrimination in the corpus.
