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Harnessing social media data for analyzing public inconvenience in construction of Indian metro rail projects

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Abstract

The metro rail links many parts of a large city and offers one of the best modes of transit across it. However, the construction phase of the metro causes inconveniences to the people living in cities by significantly escalating the noise and dust pollution. During the construction of metro rails, citizens face problems in their everyday lives, especially as the elevated corridors go through thick-populated areas and high-vehicle traffic areas, creating traffic snarls and impediments. The literature review revealed additional concerns, such as public green cover depletion, potholes, building waste disposal, and vibrational issues. With the advent of social media, urban citizens use platforms like Twitter to express their opinions on inconveniences. The interactions over these social media platforms constitute big data. This data has immense potential for public engagement, accountability, and timely resolution of public inconvenience. The examination and analysis of social media posts on these issues are important as such analysis would inform the metro rail agency about the factors that affect the public and their emotional reaction to a specific activity or series of activities performed by the construction team. In this work, Twitter posts about the inconveniences associated with metro rail projects in four cities across India were analyzed. Social network analysis (SNA), text analytics, topic modeling, and sentiment analysis were conducted to analyze the data. SNA helped find the Twitter accounts with above-average betweenness centralities, while text analytics and topic modeling helped find latent discussion topics among the stakeholders. Sentiment analysis gave an idea of the public sentiments towards the projects.

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Correspondence to Srinjoy Das.

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Das, S., Devkar, G. Harnessing social media data for analyzing public inconvenience in construction of Indian metro rail projects. CSIT 10, 107–120 (2022). https://doi.org/10.1007/s40012-022-00356-9

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