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

Reviewer: Guanlan Zhang

Inviter role(s): EDITOR

Publication date of review: 2023-02-08

Guanlan Zhang4

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

Despite some minor mistakes, the paper has a solid elaboration on main topic with high confidence.

Average rating:	    Rated 4 of 5.
Level of importance:	    Rated 4 of 5.
Level of validity:	    Rated 4 of 5.
Level of completeness:	    Rated 4 of 5.
Level of comprehensibility:	    Rated 4 of 5.
Competing interests:	None

Reviewed article

Record: found
Abstract: found
Article: found

Is Open Access

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

Ruiqiu YAO, Andrew Gillen (2022)

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.

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Preprint version 1

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Review information

DOI:: 10.14293/S2199-1006.1.SOR-ENG.AEG3YW.v1.RPMISX

License:

This work has been published open access under Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com.

ScienceOpen disciplines: Engineering,Civil engineering

Keywords: Public opinion evaluation,Sentiment analysis,Transport,Policy and law,Environmental policy and practice,Machine learning,Civil infrastructure projects,Topic modelling,Sustainability

Review text

Summary: in this work, the author proposed a learning-based framework to evaluate public opinion through social media platform. Most of the contents are presented clearly with a proper use of language. The methods effectively solve the problem, and the experimental results are acceptable.

Comments.
1, there are symbols not correct in math formulas. In Eq.1), the x_1 and p(xn|y) are not in correct form.
2, the state-of-the-art methods are not clearly stated and the comparison between the proposed method and the SOTA is not verified. What is the significance of this work over previous work?
3, in section 3.2.2, on what machine do you train your model and what is the time consumption?
4, the training results in section 3.2.2 is not very good. Have you consider using deep neural networks to solve the problem?
5, how to evaluate the accuracy of sentiment analysis and topic modeling?

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Preprint version 2

Preprint version 1

Reviewed by Kwadwo Agyapon-Ntra Reviewed by Chrisina Jayne Reviewed by Guanlan Zhang