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^*

^*Bu çalışma için yazışmadan sorumlu yazar

İşletme Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

Özet

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.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Industrial Engineering in the Industry 4.0 Era - Selected Papers from ISPR2023
Editörler	Numan M. Durakbasa, M. Güneş Gençyılmaz
Yayınlayan	Springer Science and Business Media Deutschland GmbH
Sayfalar	3-15
Sayfa sayısı	13
ISBN (Basılı)	9783031539909
DOI'lar	https://doi.org/10.1007/978-3-031-53991-6_1
Yayın durumu	Yayınlandı - 2024
Etkinlik	International Symposium for Production Research, ISPR 2023 - Antalya, Turkey Süre: 5 Eki 2023 → 7 Eki 2023

Yayın serisi

Adı	Lecture Notes in Mechanical Engineering
ISSN (Basılı)	2195-4356
ISSN (Elektronik)	2195-4364

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	International Symposium for Production Research, ISPR 2023
Ülke/Bölge	Turkey
Şehir	Antalya
Periyot	5/10/23 → 7/10/23

Bibliyografik not

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

Belgeye Erişim

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

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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. editör / Numan M. Durakbasa ; M. Güneş Gençyılmaz. Springer Science and Business Media Deutschland GmbH, 2024. pp. 3-15 (Lecture Notes in Mechanical Engineering).

@inproceedings{25a7448303bb416d9cd7cc8c9d4be2df,

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",

publisher = "Springer Science and Business Media Deutschland GmbH",

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).

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

TY - GEN

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.

KW - latent dirichlet allocation

KW - public transportation

KW - roberta

KW - sentiment analysis

KW - topic modeling

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U2 - 10.1007/978-3-031-53991-6_1

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

M3 - Conference contribution

AN - SCOPUS:85187796658

SN - 9783031539909

T3 - Lecture Notes in Mechanical Engineering

SP - 3

EP - 15

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

A2 - Durakbasa, Numan M.

A2 - Gençyılmaz, M. Güneş

PB - Springer Science and Business Media Deutschland GmbH

T2 - International Symposium for Production Research, ISPR 2023

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, editörler, 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

Özet

Yayın serisi

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Bibliyografik not

Belgeye Erişim

Diğer Dosyalar ve Linkler

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