Topic Modeling and Sentiment Analysis of Electric Vehicles of Twitter Data
H. P. Suresha, Krishna Kumar Tiwari
Asian Journal of Research in Computer Science · pp. 13–29 · Published 8 Oct 2021
10.9734/ajrcos/2021/v12i230278Abstract
Twitter is a well-known social media tool for people to communicate their thoughts and feelings about products or services. In this project, I collect electric vehicles related user tweets from Twitter using Twitter API and analyze public perceptions and feelings regarding electric vehicles. After collecting the data, To begin with, as the first step, I built a pre-processed data model based on natural language processing (NLP) methods to select tweets. In the second step, I use topic modeling, word cloud, and EDA to examine several aspects of electric vehicles. By using Latent Dirichlet allocation, do Topic modeling to infer the various topics of electric vehicles. The topic modeling in this study was compared with LSA and LDA, and I found that LDA provides a better insight into topics, as well as better accuracy than LSA.In the third step, the “Valence Aware Dictionary (VADER)” and “sEntiment Reasoner (SONAR)” are used to analyze sentiment of electric vehicles, and its related tweets are either positive, negative, or neutral. In this project, I collected 45000 tweets from Twitter API, related hashtags, user location, and different topics of electric vehicles. Tesla is the top hashtag Twitter users tweeted while sharing tweets related to electric vehicles. Ekero Sweden is the most common location of users related to electric vehicles tweets. Tesla is the most common word in the tweets related to electric vehicles. Elon-musk is the common bi-gram found in the tweets related to electric vehicles. 47.1% of tweets are positive, 42.4% are neutral, and 10.5% are negative as per VADER Finally, I deploy this project work as a fully functional web app.
Cited by 15
Ondrej Havran, D. Watling, Hai-Bo Chen · Travel Behaviour & Society · 2026
Dwi Adi Purnama, Zelania In Haryanto, A. R. Anugerah · Journal of Open Innovation: Technology, Market and Complexity · 2026
Dwi Adi Purnama, Distian Pingkan Lumi, Atik Febriani · Journal of Open Innovation: Technology, Market and Complexity · 2025
A. Mourtzouchou, A. L. Marin, Lorenzo Laveneziana · Scientific Reports · 2025
Aliffia Hanifah, Muhardi Saputra, R. Y. Fa'rifah · 2025 4th International Conference on Electronics Representation and Algorithm (ICERA) · 2025
Novialdi Ashari, Mokhamad Zukhruf Mifta Al Firdaus, I. Budi · 2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) · 2023
Laina Farsiah, Alim Misbullah, H. Husaini · Cyberspace: Jurnal Pendidikan Teknologi Informasi · 2022
Suparyati Suparyati, Emma Utami, Agus Fathurahman · JOURNAL OF APPLIED INFORMATICS AND COMPUTING · 2022
J. Everts, Xuan Jiang · arXiv.org · 2021
S. Mathew, Kadhim Hayawi, Faseela Abdullakutty · Data and Information Management · 2026
Related research
- Review of Airbag Injuries: A Sri Lankan Case Series — shares topic coverage
- Detecting Dental Caries through Captured Images Using the Machine Learning Technology Teachable Machine — shares topic coverage
- Prediction of Radiotherapy Dose Distribution for Glioblastoma Using Convolutional Neural Network Model — shares topic coverage
- A Systematic Literature Review of Machine Learning Methods in Healthcare — shares topic coverage
- Diagnostic Accuracy of Artificial Intelligence for Breast Cancer Detection: A Systematic Review — shares topic coverage
Article metrics
Real usage data collected on this platform.
0
Page views
0
PDF downloads
0
Outbound clicks
15
Citations
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
No views recorded yet.
Traffic sources
Referring site, by host.
No traffic recorded yet.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.