Sentiment Text Classification and Part of Speech (SCPOS) datasets

SCPOS数据集是由横滨国立大学的研究团队创建，旨在支持情感分析研究，特别是探索文本情感极性和词性情感极性之间的关系。该数据集包含四个子集，每个子集都基于现有的情感分类数据集进行标注，重点关注影响文本整体情感极性的词汇。数据集的创建过程中，研究团队采用了手动标注和基于规则的方法，确保数据的高质量和准确性。SCPOS数据集的应用领域主要集中在情感分析和词性标注，旨在通过分析词汇的情感极性来提高情感分类模型的性能。

The SCPOS dataset was developed by a research team from Yokohama National University to support sentiment analysis research, particularly the exploration of the relationship between text-level sentiment polarity and part-of-speech (POS) based sentiment polarity. This dataset comprises four subsets, each annotated based on existing sentiment classification datasets, with a core focus on lexical items that affect the overall sentiment polarity of the text. During the dataset construction, the research team employed both manual annotation and rule-based approaches to guarantee the high quality and accuracy of the data. The primary application domains of the SCPOS dataset are sentiment analysis and part-of-speech tagging, with the objective of enhancing the performance of sentiment classification models by analyzing the sentiment polarity of vocabulary.