User Sentiment Analysis Based on Securities Application Elements
Minji Kim1, Subeen Kim2, Yoonha Park2
1Department of Artificial Intelligence, Kyung Hee University, Yongin 17104, Republic of Korea.
Behavioral Sciences (Basel, Switzerland)
|September 28, 2024
Summary
This study introduces Aspect-Based Sentiment Analysis (ABSA) for improving Korean mobile securities applications by analyzing user reviews. ABSA uncovers specific user feedback on features like login and transactions, offering deeper design insights than traditional methods.
Area of Science:
- Natural Language Processing
- Mobile Application Design
- Sentiment Analysis
Background:
- Designing mobile securities applications presents significant challenges due to complexity.
- Analyzing online user reviews is crucial for application improvement.
- Deep learning applications for sentiment analysis of Korean text are underexplored.
Purpose of the Study:
- To explore Aspect-Based Sentiment Analysis (ABSA) for analyzing Korean securities application reviews.
- To identify critical design elements and user sentiments within these applications.
- To demonstrate ABSA as a scalable and cost-effective alternative to traditional user research.
Main Methods:
- Utilized Aspect-Based Sentiment Analysis (ABSA) on text-based user review data of Korean securities applications.
- Applied techniques including Pointwise Mutual Information (PMI), Singular Value Decomposition (SVD), and Word2Vec.
- Identified key aspects such as "update", "screen", "chart", "login", "access", "authentication", "account", and "transaction".
Main Results:
- ABSA provided deeper insights into user sentiment compared to overall ratings.
- Identified specific areas of user dissatisfaction, even in generally positive reviews.
- Highlighted critical elements influencing user experience in mobile securities applications.
Conclusions:
- ABSA is an effective method for uncovering nuanced user sentiments in mobile application design.
- This approach offers a scalable and cost-effective solution for user research in the securities application domain.
- The findings can inform future design improvements for mobile securities platforms.
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