Analyzing Technostress Factors: Aspect-Based Sentiment Analysis for Identifying Causes in Fintech Users Using the Decision Tree Algorithm

Sahra Bilqis Fauziyyah (), Muhardi Saputra and Riska Yanu Fa’rifah
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Sahra Bilqis Fauziyyah: Telkom University
Muhardi Saputra: Telkom University
Riska Yanu Fa’rifah: Telkom University

A chapter in Proceedings of the International Conference on Enterprise and Industrial Systems (ICOEINS 2023), 2023, pp 98-106 from Springer

Abstract: Abstract Information technology innovation, particularly in Financial Technology (fintech), plays a central role in various aspects of life. Among the fintech services, e-wallets are highly popular in Indonesia. In 2021, OVO was a leading e-wallet; however, in 2022, it experienced a decline, suspected to be caused by technostress. People who experience technostress have negative attitudes and feelings towards technology. This research employs Aspect-Based Sentiment Analysis, using LDA topic modeling to identify four aspects: features, access, service, and security. OVO user reviews from Google Play Store were scraped for data analysis. Sentiment classification using C4.5 Decision Tree with a 75:25 data sharing ratio achieved high accuracies: features (96.79%), access (94.95%), service (92.19%), and security (96.36%). The results aid fintech companies, especially OVO, in addressing user technostress and enhancing user experience and engagement.

Keywords: Fintech; E-Wallet; Technostress; Aspect-Based Sentiment Analysis; LDA; Decision Tree C4.5 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.2991/978-94-6463-340-5_9

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