Analyzing Public Opinion on Electrical Vehicles in Indonesia Using Sentiment Analysis and Topic Modeling

Ashari, Novialdi; Firdaus, Mokhamad Zukhruf Mifta Al; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna

doi:10.1109/iccosite57641.2023.10127834

Cited by 3 publications

(1 citation statement)

References 10 publications

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“…This semi-finished data still needs to be corrected and formatted consistently to not interfere with the output quality. The study by Ashari et al (2023), which successfully discussed sentiment analysis regarding the Indonesian public's response to the presence of electric vehicles in general, stated that there were 55% positive responses and the remaining 45% negative. However, in his research, he did not consider neutral opinions.…”

Section: Introductionmentioning

confidence: 99%

Sentiment Analysis about Electric Motorbikes in Indonesia Using Twitter Data

Irawati,

Bellanov,

Damayanti

2024

Spek Ind

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Along with the rapid development of technology, various types of transportation have experienced increased innovation in shapes, colours,models, and even engines. However, one thing that needs special attention is the number of pollutants or emissions released by vehicles. One effort to reduce emissions is increasing the production of Battery-Based Electric Motorized Vehicles. Battery-based electric vehicles developed in Indonesia include electric cars and electric motorcycles. Among these types of electric vehicles, Indonesian society widely adopts electric motorcycles. However, sales of electric motorbikes were only 15 thousand units, lower than sales of petrol motorbikes which reached 5 million units. This study contributes to understanding further how the community responds to electric motorcycles in detail through sentiment analysis on social media data. Consumer acceptance of electric motorcycles can be seen from the numerous active Twitter users in Indonesia who provide positive and negative comments on the presence of electric motorcycles. Text information based on public comments in Indonesia via Twitter is collected using Sentiment Analysis in R Studio. Twitter comments will be classified into positive, negative, and neutral groups. The results show 63% positive, 21% unfavourable, and 14% neutral opinions. This condition means that Indonesian society accepts and has a supportive opinion of the presence of electric motorcycles. The government and entrepreneurs can use this information to create electric motorcycles that align with the community's preferences.

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Section: Introductionmentioning

confidence: 99%

Sentiment Analysis about Electric Motorbikes in Indonesia Using Twitter Data

Irawati,

Bellanov,

Damayanti

2024

Spek Ind

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Electric Vehicles in the Digital Discourse: A Sentiment Analysis of Social Media Engagement for Turkey

Durmus Senyapar

2024

Sage Open

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The adoption of electric vehicles (EVs) is a critical component of transitioning toward sustainable transportation systems. Understanding public sentiment and engagement regarding EVs is essential for policymakers, industry participants, and scholars to address challenges and opportunities in the EV market effectively. This study conducted a comprehensive analysis of public sentiment and engagement concerning EVs on social media platforms. One thousand posts from Facebook, Instagram, and X were analyzed to provide a cohesive narrative encompassing public opinion toward EVs and offering a roadmap for this disruptive technology’s future. The results indicate a significant level of user engagement, supported by 7,000 collective interactions and an impressive 4,300 shares. Predominantly positive sentiments, comprising 83.2% of the analyzed posts, highlight the widespread optimism regarding EV technology. The discourse encompasses various subjects, including brand preferences, financial implications, infrastructure, and environmental aspects. The insights gleaned from these results are of immense value to policymakers, industry participants, and scholars as they navigate the ever-changing terrain of electric mobility.

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Electric Vehicle Sentiment Analysis Using Large Language Models

Sharma,

Ud Din,

Ogunleye

2024

Analytics

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Sentiment analysis is a technique used to understand the public’s opinion towards an event, product, or organization. For example, sentiment analysis can be used to understand positive or negative opinions or attitudes towards electric vehicle (EV) brands. This provides companies with valuable insight into the public’s opinion of their products and brands. In the field of natural language processing (NLP), transformer models have shown great performance compared to traditional machine learning algorithms. However, these models have not been explored extensively in the EV domain. EV companies are becoming significant competitors in the automotive industry and are projected to cover up to 30% of the United States light vehicle market by 2030 In this study, we present a comparative study of large language models (LLMs) including bidirectional encoder representations from transformers (BERT), robustly optimised BERT (RoBERTa), and a generalised autoregressive pre-training method (XLNet) using Lucid Motors and Tesla Motors YouTube datasets. Results evidenced that LLMs like BERT and her variants are off-the-shelf algorithms for sentiment analysis, specifically when fine-tuned. Furthermore, our findings present the need for domain adaptation whilst utilizing LLMs. Finally, the experimental results showed that RoBERTa achieved consistent performance across the EV datasets with an F1 score of at least 92%.

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Analyzing Public Opinion on Electrical Vehicles in Indonesia Using Sentiment Analysis and Topic Modeling

Cited by 3 publications

References 10 publications

Sentiment Analysis about Electric Motorbikes in Indonesia Using Twitter Data

Sentiment Analysis about Electric Motorbikes in Indonesia Using Twitter Data

Electric Vehicles in the Digital Discourse: A Sentiment Analysis of Social Media Engagement for Turkey

Electric Vehicle Sentiment Analysis Using Large Language Models

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