Comparative Analysis of Public Transportation Through Sentiment Analysis and Topic Modeling

Aslıgül Aksan; Hatice Camgöz Akdağ

doi:10.1007/978-3-031-53991-6_1

Comparative Analysis of Public Transportation Through Sentiment Analysis and Topic Modeling

Aslıgül Aksan, Hatice Camgöz Akdağ^*

^*Corresponding author for this work

Department of Management Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In the modern digital age, social media emerges as a powerful tool for extracting various public opinions on a wide range of subjects. Among various platforms, Twitter stands as a comprehensive source of real-time, global sentiment analysis. This research uses Twitter’s expansive reach to delve into public opinions on public transportation in both the United Kingdom and India. Employing the RoBERTa (Robustly Optimized BERT Pretraining Approach), this study categorizes tweets into positive, neutral, and negative sentiments, offering a structured analysis of public feelings toward transportation services in these nations. Subsequent application of Latent Dirichlet Allocation (LDA) reveals the causes within the identified sentiments on specific areas of satisfaction and concern in both countries’ public transportation systems. The crucial insights obtained from this study aim to guide informed and strategic enhancements in the public transportation sectors of both nations, pinpointing exact areas that demand attention and improvement.

Original language	English
Title of host publication	Industrial Engineering in the Industry 4.0 Era - Selected Papers from ISPR2023
Editors	Numan M. Durakbasa, M. Güneş Gençyılmaz
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	3-15
Number of pages	13
ISBN (Print)	9783031539909
DOIs	https://doi.org/10.1007/978-3-031-53991-6_1
Publication status	Published - 2024
Event	International Symposium for Production Research, ISPR 2023 - Antalya, Turkey Duration: 5 Oct 2023 → 7 Oct 2023

Publication series

Name	Lecture Notes in Mechanical Engineering
ISSN (Print)	2195-4356
ISSN (Electronic)	2195-4364

Conference

Conference	International Symposium for Production Research, ISPR 2023
Country/Territory	Turkey
City	Antalya
Period	5/10/23 → 7/10/23

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Keywords

latent dirichlet allocation
public transportation
roberta
sentiment analysis
topic modeling

Access to Document

10.1007/978-3-031-53991-6_1

Cite this

Aksan, A., & Akdağ, H. C. (2024). Comparative Analysis of Public Transportation Through Sentiment Analysis and Topic Modeling. In N. M. Durakbasa, & M. G. Gençyılmaz (Eds.), Industrial Engineering in the Industry 4.0 Era - Selected Papers from ISPR2023 (pp. 3-15). (Lecture Notes in Mechanical Engineering). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-53991-6_1

Aksan, Aslıgül ; Akdağ, Hatice Camgöz. / Comparative Analysis of Public Transportation Through Sentiment Analysis and Topic Modeling. Industrial Engineering in the Industry 4.0 Era - Selected Papers from ISPR2023. editor / Numan M. Durakbasa ; M. Güneş Gençyılmaz. Springer Science and Business Media Deutschland GmbH, 2024. pp. 3-15 (Lecture Notes in Mechanical Engineering).

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title = "Comparative Analysis of Public Transportation Through Sentiment Analysis and Topic Modeling",

abstract = "In the modern digital age, social media emerges as a powerful tool for extracting various public opinions on a wide range of subjects. Among various platforms, Twitter stands as a comprehensive source of real-time, global sentiment analysis. This research uses Twitter{\textquoteright}s expansive reach to delve into public opinions on public transportation in both the United Kingdom and India. Employing the RoBERTa (Robustly Optimized BERT Pretraining Approach), this study categorizes tweets into positive, neutral, and negative sentiments, offering a structured analysis of public feelings toward transportation services in these nations. Subsequent application of Latent Dirichlet Allocation (LDA) reveals the causes within the identified sentiments on specific areas of satisfaction and concern in both countries{\textquoteright} public transportation systems. The crucial insights obtained from this study aim to guide informed and strategic enhancements in the public transportation sectors of both nations, pinpointing exact areas that demand attention and improvement.",

keywords = "latent dirichlet allocation, public transportation, roberta, sentiment analysis, topic modeling",

author = "Aslıg{\"u}l Aksan and Akdağ, {Hatice Camg{\"o}z}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; International Symposium for Production Research, ISPR 2023 ; Conference date: 05-10-2023 Through 07-10-2023",

year = "2024",

doi = "10.1007/978-3-031-53991-6_1",

language = "English",

isbn = "9783031539909",

series = "Lecture Notes in Mechanical Engineering",

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pages = "3--15",

editor = "Durakbasa, {Numan M.} and Gen{\c c}yılmaz, {M. G{\"u}ne{\c s}}",

booktitle = "Industrial Engineering in the Industry 4.0 Era - Selected Papers from ISPR2023",

address = "Germany",

}

Aksan, A & Akdağ, HC 2024, Comparative Analysis of Public Transportation Through Sentiment Analysis and Topic Modeling. in NM Durakbasa & MG Gençyılmaz (eds), Industrial Engineering in the Industry 4.0 Era - Selected Papers from ISPR2023. Lecture Notes in Mechanical Engineering, Springer Science and Business Media Deutschland GmbH, pp. 3-15, International Symposium for Production Research, ISPR 2023, Antalya, Turkey, 5/10/23. https://doi.org/10.1007/978-3-031-53991-6_1

Comparative Analysis of Public Transportation Through Sentiment Analysis and Topic Modeling. / Aksan, Aslıgül; Akdağ, Hatice Camgöz.
Industrial Engineering in the Industry 4.0 Era - Selected Papers from ISPR2023. ed. / Numan M. Durakbasa; M. Güneş Gençyılmaz. Springer Science and Business Media Deutschland GmbH, 2024. p. 3-15 (Lecture Notes in Mechanical Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Comparative Analysis of Public Transportation Through Sentiment Analysis and Topic Modeling

AU - Aksan, Aslıgül

AU - Akdağ, Hatice Camgöz

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

PY - 2024

Y1 - 2024

N2 - In the modern digital age, social media emerges as a powerful tool for extracting various public opinions on a wide range of subjects. Among various platforms, Twitter stands as a comprehensive source of real-time, global sentiment analysis. This research uses Twitter’s expansive reach to delve into public opinions on public transportation in both the United Kingdom and India. Employing the RoBERTa (Robustly Optimized BERT Pretraining Approach), this study categorizes tweets into positive, neutral, and negative sentiments, offering a structured analysis of public feelings toward transportation services in these nations. Subsequent application of Latent Dirichlet Allocation (LDA) reveals the causes within the identified sentiments on specific areas of satisfaction and concern in both countries’ public transportation systems. The crucial insights obtained from this study aim to guide informed and strategic enhancements in the public transportation sectors of both nations, pinpointing exact areas that demand attention and improvement.

AB - In the modern digital age, social media emerges as a powerful tool for extracting various public opinions on a wide range of subjects. Among various platforms, Twitter stands as a comprehensive source of real-time, global sentiment analysis. This research uses Twitter’s expansive reach to delve into public opinions on public transportation in both the United Kingdom and India. Employing the RoBERTa (Robustly Optimized BERT Pretraining Approach), this study categorizes tweets into positive, neutral, and negative sentiments, offering a structured analysis of public feelings toward transportation services in these nations. Subsequent application of Latent Dirichlet Allocation (LDA) reveals the causes within the identified sentiments on specific areas of satisfaction and concern in both countries’ public transportation systems. The crucial insights obtained from this study aim to guide informed and strategic enhancements in the public transportation sectors of both nations, pinpointing exact areas that demand attention and improvement.

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KW - roberta

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BT - Industrial Engineering in the Industry 4.0 Era - Selected Papers from ISPR2023

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Y2 - 5 October 2023 through 7 October 2023

ER -

Aksan A, Akdağ HC. Comparative Analysis of Public Transportation Through Sentiment Analysis and Topic Modeling. In Durakbasa NM, Gençyılmaz MG, editors, Industrial Engineering in the Industry 4.0 Era - Selected Papers from ISPR2023. Springer Science and Business Media Deutschland GmbH. 2024. p. 3-15. (Lecture Notes in Mechanical Engineering). doi: 10.1007/978-3-031-53991-6_1

Comparative Analysis of Public Transportation Through Sentiment Analysis and Topic Modeling

Abstract

Publication series

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Bibliographical note

Keywords

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