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

Author:

Do Sy Tien,Nguyen Viet Thanh,Banlasan Denver

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.

Publisher

Emerald

Subject

Building and Construction,Architecture,Civil and Structural Engineering,General Computer Science,Control and Systems Engineering

Reference61 articles.

1. Integration of social media in day-to-day operations of construction firms;Journal of Management in Engineering,2019

2. Data mining in social media,2011

3. Latent dirichlet allocation;Journal of Machine Learning Research,2003

4. Review paper: health monitoring of civil infrastructure;Structural Health Monitoring,2003

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3