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      Public Opinion Analysis on Social Media Platforms: A Case Study of High Speed 2 (HS2) Rail Infrastructure Project

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            Abstract

            Abstract: Public opinion evaluation is becoming increasingly significant in infrastructure project assessment. The inefficiencies of conventional evaluation approaches can be improved with social media analysis. Posts about infrastructure projects on social media provide a large amount of data for assessing public opinion. This study proposed a public opinion evaluation framework with machine learning algorithms, including sentiment analysis and topic modelling. We selected the United Kingdom railway project, High Speed 2, as the case study. The sentiment analysis showed that around 53% to 63% of tweets expressed a negative sentiment, suggesting the public may have an overall negative perception of the project. Topic modelling with text corpora showed key topics of public opinion. The proposed framework demonstrates the feasibility of using supervised machine learning to evaluate public opinion on infrastructure projects, as the framework can save time and cost. Furthermore, assessment results can aid policymakers and managers in decision-making.

            Content

            Author and article information

            Journal
            UCL Open: Environment Preprint
            UCL Press
            16 June 2022
            Affiliations
            [1 ] Civil, Environmental and Geomatic Engineering / University College London / London / the United Kingdom
            [2 ] Department of Civil and Environmental Engineering / Northeastern University / Boston / the United States
            Author notes
            Author information
            https://orcid.org/0000-0002-2596-5031
            Article
            10.14324/111.444/000154.v1
            0f5e30a7-0741-46b2-995e-154e3ae110bc

            This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY) 4.0 https://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

            History
            : 16 June 2022

            The datasets generated during and/or analysed during the current study are available in the repository: https://github.com/RichardYao08/PinionAnalysisSocialMedia
            Engineering,Civil engineering
            Civil infrastructure projects,Policy and law,Sentiment analysis,Environmental policy and practice,Machine learning,Transport,Topic modelling,Sustainability,Public opinion evaluation

            Comments

            Date: 18 April 2023

            Handling Editor: Prof Dan Osborn

            Editorial decision: Request revision. The Handling Editor requested revisions; the article has been returned to the authors to make this revision.

            2023-04-18 16:20 UTC
            +1
            One person recommends this

            Date: 12 July 2022

            Handling Editor: Prof Dan Osborn

            This article is a preprint article and has not been peer-reviewed. It is under consideration following submission to UCL Open: Environment for open peer review.

            2022-07-12 10:47 UTC
            +1
            One person recommends this

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