SentiHood

SentiHood数据集是由伦敦大学学院创建，用于城市邻里目标方面情感分析。该数据集从问答平台提取，涉及用户对城市邻里多个方面的讨论。数据集包含5215条句子，涉及居住、安全、价格等多个方面，旨在通过细粒度情感分析帮助用户更深入理解城市邻里的质量。创建过程中，使用了BRAT标注工具，确保了数据的高质量标注。该数据集适用于自然语言处理领域，特别是情感分析和城市规划研究。

The SentiHood dataset was developed by University College London (UCL) for aspect-based sentiment analysis targeting urban neighborhoods. Extracted from question-and-answer platforms, the dataset covers users' discussions on multiple aspects of urban neighborhoods. It contains 5,215 sentences involving aspects such as housing, safety, and living costs, with the goal of helping users gain a deeper comprehension of urban neighborhood quality through fine-grained sentiment analysis. During the dataset's construction, the BRAT annotation tool was employed to ensure high-quality annotation of the data. This dataset has applications in the field of natural language processing, particularly for sentiment analysis and urban planning research.