Next Article in Journal
The Group Intertemporal Decision-Making Process
Previous Article in Journal
Grow Your Own School Mental Health Specialists: A Policy Pilot to Address Behavioral Health Workforce Shortages in Schools
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Behavioral Sciences
Volume 14
Issue 9
10.3390/bs14090814
behavsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

User Sentiment Analysis Based on Securities Application Elements

by
Minji Kim
1,
Subeen Kim
2,
Yoonha Park
2,
Sangwoo Bahn
2,*,
Sung Hee Ahn
3,* and
Bhavadharani NambiNarayanan
2
1
Department of Artificial Intelligence, Kyung Hee University, Yongin 17104, Republic of Korea
2
Department of Industrial and Management Systems Engineering, Kyung Hee University, Yongin 17104, Republic of Korea
3
Department of Bigdata and Management Engineering, Namseoul University, Cheonan 31020, Republic of Korea
*
Authors to whom correspondence should be addressed.
Behav. Sci. 2024, 14(9), 814; https://doi.org/10.3390/bs14090814
Submission received: 23 June 2024 / Revised: 24 August 2024 / Accepted: 10 September 2024 / Published: 13 September 2024
Browse Figures
Review Reports Versions Notes

Abstract

Designing securities applications for mobile devices is challenging due to their inherent complexity, necessitating improvement through the analysis of online reviews. However, research applying deep learning techniques to the sentiment analysis of Korean text remains limited. This study explores the use of Aspect-Based Sentiment Analysis (ABSA) as an effective alternative to traditional user research methods for securities application design. By analyzing large volumes of text-based user review data of Korean securities applications, the study identifies critical elements like “update”, “screen”, “chart”, “login”, “access”, “authentication”, “account”, and “transaction”, revealing nuanced user sentiments through techniques such as PMI, SVD, and Word2Vec. ABSA offers deeper insights compared to overall ratings, uncovering hidden areas of dissatisfaction despite positive biases in reviews. This research demonstrates the scalability and cost-effectiveness of ABSA in mobile-application design research.
Keywords: aspect-based sentiment analysis; user review; securities application aspect-based sentiment analysis; user review; securities application

Share and Cite

MDPI and ACS Style

Kim, M.; Kim, S.; Park, Y.; Bahn, S.; Ahn, S.H.; NambiNarayanan, B. User Sentiment Analysis Based on Securities Application Elements. Behav. Sci. 2024, 14, 814. https://doi.org/10.3390/bs14090814

AMA Style

Kim M, Kim S, Park Y, Bahn S, Ahn SH, NambiNarayanan B. User Sentiment Analysis Based on Securities Application Elements. Behavioral Sciences. 2024; 14(9):814. https://doi.org/10.3390/bs14090814

Chicago/Turabian Style

Kim, Minji, Subeen Kim, Yoonha Park, Sangwoo Bahn, Sung Hee Ahn, and Bhavadharani NambiNarayanan. 2024. "User Sentiment Analysis Based on Securities Application Elements" Behavioral Sciences 14, no. 9: 814. https://doi.org/10.3390/bs14090814

APA Style

Kim, M., Kim, S., Park, Y., Bahn, S., Ahn, S. H., & NambiNarayanan, B. (2024). User Sentiment Analysis Based on Securities Application Elements. Behavioral Sciences, 14(9), 814. https://doi.org/10.3390/bs14090814

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop