Birleşik Krallik'taki Toplu Taşima Hakkindaki Kamuoyu Görüşleri: Duygu Analizi ve Konu Modellemesi

Asligul Aksan; Hatice Camgöz Akdaǧ

doi:10.1109/SIU59756.2023.10223775

Birleşik Krallik'taki Toplu Taşima Hakkindaki Kamuoyu Görüşleri: Duygu Analizi ve Konu Modellemesi

Translated title of the contribution: Public Opinion on UK Public Transportation Through Sentiment Analysis and Topic Modeling

Asligul Aksan, Hatice Camgöz Akdaǧ

Department of Management Engineering

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

1 Citation (Scopus)

Abstract

Social media has become a valuable data source for gathering and analyzing public opinion on products and services. Among the popular social media platforms, Twitter stands out for its ability to provide place-time information in a text format called tweets. In this study, sentiment analysis and topic modeling of tweets related to public transportation in the United Kingdom were analyzed. Using the Robustly Optimized BERT Pretraining Approach (RoBERTa), tweets are divided according to their polarities: positive, neutral, and negative. Additionally, Latent Dirichlet Allocation (LDA) is applied to positive and negative tweets, and topics providing the causes are obtained. These topics reveal the strengths and weaknesses of the United Kingdom's public transportation service.

Translated title of the contribution	Public Opinion on UK Public Transportation Through Sentiment Analysis and Topic Modeling
Original language	Turkish
Title of host publication	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350343557
DOIs	https://doi.org/10.1109/SIU59756.2023.10223775
Publication status	Published - 2023
Event	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023 - Istanbul, Turkey Duration: 5 Jul 2023 → 8 Jul 2023

Publication series

Name	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023

Conference

Conference	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023
Country/Territory	Turkey
City	Istanbul
Period	5/07/23 → 8/07/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/SIU59756.2023.10223775

Cite this

Aksan, A., & Akdaǧ, H. C. (2023). Birleşik Krallik'taki Toplu Taşima Hakkindaki Kamuoyu Görüşleri: Duygu Analizi ve Konu Modellemesi. In 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023 (31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU59756.2023.10223775

Aksan, Asligul ; Akdaǧ, Hatice Camgöz. / Birleşik Krallik'taki Toplu Taşima Hakkindaki Kamuoyu Görüşleri : Duygu Analizi ve Konu Modellemesi. 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023).

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title = "Birle{\c s}ik Krallik'taki Toplu Ta{\c s}ima Hakkindaki Kamuoyu G{\"o}r{\"u}{\c s}leri: Duygu Analizi ve Konu Modellemesi",

abstract = "Social media has become a valuable data source for gathering and analyzing public opinion on products and services. Among the popular social media platforms, Twitter stands out for its ability to provide place-time information in a text format called tweets. In this study, sentiment analysis and topic modeling of tweets related to public transportation in the United Kingdom were analyzed. Using the Robustly Optimized BERT Pretraining Approach (RoBERTa), tweets are divided according to their polarities: positive, neutral, and negative. Additionally, Latent Dirichlet Allocation (LDA) is applied to positive and negative tweets, and topics providing the causes are obtained. These topics reveal the strengths and weaknesses of the United Kingdom's public transportation service.",

keywords = "public transportation, sentiment analysis, topic modelling",

author = "Asligul Aksan and Akdaǧ, {Hatice Camg{\"o}z}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023 ; Conference date: 05-07-2023 Through 08-07-2023",

year = "2023",

doi = "10.1109/SIU59756.2023.10223775",

language = "T{\"u}rk{\c c}e",

series = "31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023",

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Aksan, A & Akdaǧ, HC 2023, Birleşik Krallik'taki Toplu Taşima Hakkindaki Kamuoyu Görüşleri: Duygu Analizi ve Konu Modellemesi. in 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023. 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023, Institute of Electrical and Electronics Engineers Inc., 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023, Istanbul, Turkey, 5/07/23. https://doi.org/10.1109/SIU59756.2023.10223775

Birleşik Krallik'taki Toplu Taşima Hakkindaki Kamuoyu Görüşleri: Duygu Analizi ve Konu Modellemesi. / Aksan, Asligul; Akdaǧ, Hatice Camgöz.
31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023).

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

TY - GEN

T1 - Birleşik Krallik'taki Toplu Taşima Hakkindaki Kamuoyu Görüşleri

T2 - 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023

AU - Aksan, Asligul

AU - Akdaǧ, Hatice Camgöz

PY - 2023

Y1 - 2023

N2 - Social media has become a valuable data source for gathering and analyzing public opinion on products and services. Among the popular social media platforms, Twitter stands out for its ability to provide place-time information in a text format called tweets. In this study, sentiment analysis and topic modeling of tweets related to public transportation in the United Kingdom were analyzed. Using the Robustly Optimized BERT Pretraining Approach (RoBERTa), tweets are divided according to their polarities: positive, neutral, and negative. Additionally, Latent Dirichlet Allocation (LDA) is applied to positive and negative tweets, and topics providing the causes are obtained. These topics reveal the strengths and weaknesses of the United Kingdom's public transportation service.

AB - Social media has become a valuable data source for gathering and analyzing public opinion on products and services. Among the popular social media platforms, Twitter stands out for its ability to provide place-time information in a text format called tweets. In this study, sentiment analysis and topic modeling of tweets related to public transportation in the United Kingdom were analyzed. Using the Robustly Optimized BERT Pretraining Approach (RoBERTa), tweets are divided according to their polarities: positive, neutral, and negative. Additionally, Latent Dirichlet Allocation (LDA) is applied to positive and negative tweets, and topics providing the causes are obtained. These topics reveal the strengths and weaknesses of the United Kingdom's public transportation service.

KW - public transportation

KW - sentiment analysis

KW - topic modelling

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DO - 10.1109/SIU59756.2023.10223775

M3 - Konferans katkısı

AN - SCOPUS:85173460177

T3 - 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023

BT - 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 5 July 2023 through 8 July 2023

ER -

Aksan A, Akdaǧ HC. Birleşik Krallik'taki Toplu Taşima Hakkindaki Kamuoyu Görüşleri: Duygu Analizi ve Konu Modellemesi. In 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023). doi: 10.1109/SIU59756.2023.10223775

Birleşik Krallik'taki Toplu Taşima Hakkindaki Kamuoyu Görüşleri: Duygu Analizi ve Konu Modellemesi

Abstract

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Bibliographical note

UN SDGs

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