Comparative sentiment analysis of Shopee and Tokopedia in Indonesia: Insights from twitter data

Jumbri, Isma Addi and Kurnianingrum, Dian and Utama, Iston Dwija (2025) Comparative sentiment analysis of Shopee and Tokopedia in Indonesia: Insights from twitter data. Paper Asia, 41 (5b). pp. 261-274. ISSN 0218-4540

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Abstract

Understanding user sentiment is essential for strengthening platform competitiveness in Southeast Asia's rapidly evolving e-commerce landscape. This study presents a comparative sentiment analysis of Indonesia's two leading e-commerce platforms, Shopee and Tokopedia, based on 6,336 tweets collected from Twitter (X) between 10 and 17 January 2024. A lexicon-based sentiment analysis, complemented by keyword analysis, was employed to classify user sentiments using a five-star scale, thereby capturing nuanced emotional expressions. The results indicate that 47% of Shopee-related tweets conveyed positive sentiment, whereas only 15.6% of Tokopedia-related tweets were positive. In contrast, Tokopedia demonstrated a significantly higher proportion of negative sentiment at 64.3%, indicating notable user dissatisfaction. Keyword analysis revealed that Shopee users focused on affordability, promotions, and product discovery, while Tokopedia discussions emphasized transactional reliability, peer-topeer selling, and financial services. These findings suggest that Shopee should continue leveraging promotional strategies while addressing technical reliability to maintain user trust and loyalty. Meanwhile, Tokopedia must enhance logistical performance, strengthen seller accountability, and improve financial services governance to rebuild user confidence. This study contributes to the e-commerce and social media analytics literature by integrating sentiment intensity and thematic keyword analysis, offering actionable recommendations for enhancing user engagement in Indonesia's competitive digital marketplace. Future research should consider more extended observation periods and cross-platform analyses to capture evolving sentiment trends and inform strategic decision-making.

Item Type:	Article
Uncontrolled Keywords:	Sentiment analysis, E-commerce, Twitter data, User satisfaction, Social media analytics
Divisions:	Faculty of Technology Management and Technopreneurship
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	23 Feb 2026 02:03
Last Modified:	23 Feb 2026 02:03
URI:	http://eprints.utem.edu.my/id/eprint/29493
Statistic Details:	View Download Statistic

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