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

Asligul Aksan, Hatice Camgöz Akdaǧ

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

1 Atıf (Scopus)

Özet

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.

Tercüme edilen katkı başlığıPublic Opinion on UK Public Transportation Through Sentiment Analysis and Topic Modeling
Orijinal dilTürkçe
Ana bilgisayar yayını başlığı31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)9798350343557
DOI'lar
Yayın durumuYayınlandı - 2023
Etkinlik31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023 - Istanbul, Turkey
Süre: 5 Tem 20238 Tem 2023

Yayın serisi

Adı31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023

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???event.eventtypes.event.conference???31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023
Ülke/BölgeTurkey
ŞehirIstanbul
Periyot5/07/238/07/23

Bibliyografik not

Publisher Copyright:
© 2023 IEEE.

Keywords

  • public transportation
  • sentiment analysis
  • topic modelling

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