使用基于词典的方法进行情绪分析在葡萄牙里斯本,葡萄牙
Iuria Betco1, Ana Isabel Ribeiro2, David S Vale3
1Centre of Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon.
Geospatial health
|April 24, 2025
概括
对社交媒体数据的情绪分析显示,葡萄牙人在里斯本的休和消费空间表达了积极的情绪. 然而,词汇的局限性可能会影响负面情绪识别的准确性.
科学领域:
- 计算社会科学 计算社会科学
- 空间分析 空间分析
- 自然语言处理自然语言处理.
背景情况:
- 来自不同情绪状态的用户的数字数据的扩散为空间研究带来了机遇和挑战.
- 分析大量用户生成的数据需要先进的技术,如情绪分析,以提取有意义的见解.
- 了解城市空间中的公众情绪对于城市规划和社会研究至关重要.
研究的目的:
- 为了确定里斯本的城市位置,主要表现出积极或消极的公众情绪.
- 为了利用空间研究应用的社交媒体数据进行情绪分析.
- 探索特定类型的城市空间与普遍的情感色调之间的相关性.
主要方法:
- 使用加拿大国家研究委员会 (NRC) 的情感和情感词典 (EmoLex) 进行文本分析.
- 分析了来自社交媒体平台Twitter (现在是X) 的数据.
- 将情绪得分映射到里斯本的地理位置.
主要成果:
- 葡萄牙用户在与休和消费相关的领域表现出积极的情绪,包括博物馆,活动场所,花园,购物中心,商店和餐馆.
- 该研究发现了负面情绪评分中的偏见,原因是语境理解中的词典挑战.
- 特定的单词,即使在中立的背景下,有时也会被错误地赋予负分数 (例如",战争"",终端").
结论:
- 里斯本的休和消费空间与公众的积极情绪有关.
- 情感分析的准确性,特别是对负面情绪的准确性,可能会受到词汇限制和上下文模两可的影响.
- 未来的研究应该解决情绪词典中的上下文细微差别,以便更精确地进行空间情绪分析.
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