Crowdsourcing the perceived urban built environment via social media: The case of underutilized land
Crowdsourcing the perceived urban built environment via social media: The case of underutilized land
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DOI：
10.1016/j.aei.2021.101371
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发表时间：
2021-10
期刊：
影响因子：
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通讯作者：
Yan Wang;Shangde Gao;Nan Li;Siyu Yu
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文献类型：
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作者：
Yan Wang;Shangde Gao;Nan Li;Siyu Yu
众包公众对真实的建筑环境的看法，使基础设施和土地使用规划的反应更加灵敏和灵活。社交媒体已经成为公民、工程师和规划师透明地交流意见和感受的有效平台。然而，一个全面的术语资源的感知建成环境（BE）的一致的数据收集和一个特定的分析框架仍然缺乏，特别是对于不同的未充分利用的土地问题。为了填补这一知识空白，我们展示了BE特定的长期建设和扩展方法，专门用于收集Twitter数据，并提出了一个地理主题情感分析框架，检索和分析相关的推文。我们进行了一个示范性的研究，在美国的10个大都市的统计区域的未利用的土地相关的BE条款的研究结果揭示了未充分利用的土地环境的内容和情绪的空间变化，可能需要更多的本地化的努力，以解决特定的土地利用问题，在不同的城市背景。这项研究表明，Twitter作为一个有用的平台，在众包感知的BE和情绪在精细的时间和空间尺度及时。它通过调查社交媒体在环境规划中的作用，并为工程实践提出集成的特定领域数据分析方法，为工程信息学做出了贡献。
Crowdsourcing the public’s perceptions of the built environment in real time enables more responsive and agile infrastructure and land use planning. Social media has emerged to be an effective platform for citizens, engineers, and planners to communicate opinions and feelings transparently. However, a comprehensive terminological resource of the perceived built environment (BE) for consistent data collection and a specified analytical framework are still lacking, particularly for different underutilized land issues. To fill this knowledge gap, we demonstrate a BE-specific term construction and expansion method specifically for collecting Twitter data and propose a Geo-Topic-Sentiment analytical framework for retrieving and analyzing relevant tweets. We conduct a demonstrative study on un(der)utilized land-related BE terms across ten metropolitan statistical areas in the U.S. Findings reveal spatial variations in contents and sentiments about underutilized land environments, and more localized efforts may be required to address specific land use issues across different urban contexts. The research demonstrates Twitter as a useful platform in crowdsourcing perceived BE and sentiments at fine temporal and spatial scales in a timely manner. It contributes to engineering informatics by investigating the role of social media in environmental planning and proposing integrated domain-specific data analytic approaches for engineering practices.