Social media sensing framework for urban infrastructure management: a Philippine case study

IF 3.1 Q2 CONSTRUCTION & BUILDING TECHNOLOGY Construction Innovation-England Pub Date : 2023-02-08 DOI:10.1108/ci-04-2022-0082
S. T. Do, V. Nguyen, Denver Banlasan
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Abstract

Purpose This study aims to use social media data mining to revitalize and support existing urban infrastructure monitoring strategies by extracting valuable insights from public opinion, as current strategies struggle with issues such as adaptability to changing conditions, public engagement and cost effectiveness. Design/methodology/approach Twitter messages or “Tweets” about public infrastructure in the Philippines were gathered and analyzed to discover reoccurring concerns in public infrastructure, emerging topics in public debates and the people’s general view of infrastructure services. Findings This study proposes a topic model for extracting dominating subjects from aggregated social media data, as well as a sentiment analysis model for determining public opinion sentiment toward various urban infrastructure components. Originality/value The findings of this study highlight the potential of social media data mining to go beyond the limitations of traditional data collection techniques, as well as the importance of public opinion as a key driver for more user-involved infrastructure management and as an important social aspect that can be used to support planning and response strategies in routine maintenance, preservation and improvement of urban infrastructure systems.
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城市基础设施管理的社会媒体感知框架:菲律宾案例研究
目的本研究旨在利用社交媒体数据挖掘,通过从公众舆论中提取有价值的见解,振兴和支持现有的城市基础设施监测战略,因为当前的战略正在与适应变化的条件、公众参与和成本效益等问题作斗争。收集和分析了关于菲律宾公共基础设施的设计/方法/方法推特消息或“推特”,以发现公共基础设施中反复出现的问题、公共辩论中新出现的话题以及人们对基础设施服务的普遍看法。发现这项研究提出了一个主题模型,用于从聚合的社交媒体数据中提取主导主题,以及一个情绪分析模型,用于确定公众对各种城市基础设施组成部分的情绪。原创性/价值本研究的发现突出了社交媒体数据挖掘超越传统数据收集技术局限性的潜力,以及公众舆论作为更多用户参与的基础设施管理的关键驱动因素的重要性,以及作为可用于支持日常维护中的规划和响应策略的重要社会方面的重要性,保护和改善城市基础设施系统。
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来源期刊
Construction Innovation-England
Construction Innovation-England CONSTRUCTION & BUILDING TECHNOLOGY-
CiteScore
7.10
自引率
12.10%
发文量
71
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