将社交媒体数据与地理空间信息联系起来,以分析在地表水环境中和沿着地表水环境的人类情绪的变化
Kai-Ti Wu1,2, Markus Venohr3, Linda See4
1Humbolt Universität zu Berlin, Derpartment of Geography, Unter den Linden 6, Berlin 10099, Germany.
MethodsX
|September 23, 2025
概括
分析社交媒体数据揭示了公众对淡水生态系统的看法. 这项研究提供了一种方法来理解人类的情绪反应及其与水体的联系,以便更好地管理环境.
科学领域:
- 环境科学 环境科学
- 社会科学 社会科学 社会科学
- 数据科学数据科学数据科学
背景情况:
- 社交媒体数据提供了关于自然环境的人类活动和情绪的见解.
- 了解公众对淡水生态系统的看法对于有效管理和开发至关重要.
- 传统的调查方法往往不足或资源密集,以捕捉这些情绪.
研究的目的:
- 提出一种可复制的方法来分析地理位置的社交媒体数据 (Twitter),以了解公众对淡水生态系统的情绪.
- 确定与水体有关的公共情绪的空间和时间趋势.
- 确定影响这些情绪反应的关键驱动因素.
主要方法:
- 采集并清理使用Twitter API从德国 (2011-2018) 收集和清理地理位置的Twitter数据.
- 应用语言检测和基于词典的情绪分析 (多语种) 适用于短文本的社交媒体数据.
- 集成的地理空间丰富与上下文数据,如天气和人口密度.
主要成果:
- 开发了一个处理社交媒体数据的工作流程,以衡量公众对淡水环境的情绪.
- 确定了与特定水体和地点相关的情绪反应模式.
- 突出影响公众对淡水生态系统的感知和情感联系的因素.
结论:
- 社交媒体数据为了解公众对淡水生态系统的情绪提供了有价值的,可扩展的资源.
- 开发的方法允许将公众观点纳入环境管理和区域规划.
- 这种方法可以通过结合各种人类价值观和情绪反应来加强生态系统的管理.
关键词:
数据的清理数据的清理.淡水生态学 淡水生态学大规模数据的大规模数据.社交媒体数据数据他们的推特是Twitter.一个X个X个X个生态系统服务生态系统服务情绪分析是一种情绪分析.福利 幸福 幸福 幸福更多相关视频
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