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Utilizing the Twitter social media to identify transportation-related grievances in Indian cities

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Abstract

Due to population growth and rapid urbanization in Indian cities, transportation has evolved as a critical concern affecting a large number of commuters everyday. Hence it is important for the urban planners, policymakers, and transportation authorities of India to know about the different public grievances/concerns regarding transportation. This study aims to uncover valuable information about specific transport-related complaints/grievances in Indian cities from the vast pool of user-generated content on social media platforms such as Twitter. As an initial step, we have explored the broad sentiment of commuters in six Indian metropolitan cities about the existing transportation systems, and created a dataset that broadly classify tweets into negative and positive sentiments. Next, we have identified a set of fine-grained complaints/grievances in these tweets, and thus created the first dataset containing transport-related tweets labelled into various specific complaints/grievances in a multi-label setting. To our knowledge, there is no existing dataset that labels tweets according to specific concerns raised in the posts. We apply several classification models on the dataset, for classifying transportation-related tweets into the specific complaints/grievances. We further conducted a city-wise analysis to better comprehend the specific transport-related complaints prevalent in each Indian city.

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Data Availability

After acceptance of the manuscript, Data link will be rovided within the manuscript which is publicly accessible.

Competing interests

The authors declare no competing interests.

Notes

  1. We had intended to collect more data periodically to understand the persistence of grievances, seasonal variations in grievances, etc. However, Twitter changed its data policy and restricted free data collection through its API in early April 2023 (Bell 2023), thus disabling us from collecting more data.

  2. https://pypi.org/project/demoji/.

  3. https://platform.openai.com/docs/models/gpt-3-5-turbo.

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Authors and Affiliations

Authors

Contributions

Rahul P , A. Das, T. Jaiswal, V. Singh are responsible for data collection, preparation of dataset for model building, implementation of different models. S. Poddar is responsible for some model implementations, S. Ghosh is involved in research problem formulation, analysis of the problem and review of manuscript. M. Basu has contributed in analysis of the research problem, literature survey, city wise summarization of grievances and manuscript writing.

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Correspondence to Moumita Basu.

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Pullanikkat, R., Poddar, S., Das, A. et al. Utilizing the Twitter social media to identify transportation-related grievances in Indian cities. Soc. Netw. Anal. Min. 14, 118 (2024). https://doi.org/10.1007/s13278-024-01278-x

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