Fintech Sentiment Analysis using Deep Learning Approaches: a Survey

被引:0
作者
Anis, Sarah [1 ]
Morsey, Mohamed Mabrouk [1 ]
Aref, Mostafa [1 ]
机构
[1] Ain Shams Univ, Fac Comp & Informat Sci, Cairo, Egypt
来源
2024 5TH INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, ROBOTICS AND CONTROL, AIRC 2024 | 2024年
关键词
Sentiment Analysis; Deep Learning; Fintech; Natural Language Processing;
D O I
10.1109/AIRC61399.2024.10671866
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The number of consumers who are eager to use mobile financial services for their daily financial activities has increased dramatically thanks to fintech (financial technology). The success of these applications is highly dependent on user feedback. Sentiment analysis is a powerful tool for learning about users' opinions towards various applications, including fintech services. Recent studies have shown that deep learning models offer a potential way to address the difficulties in sentiment analysis. This study provides a comprehensive study of the latest deep learning approaches applied for sentiment analysis in the financial sector. The aim of this study is to give scholars and academics a broad perspective on using deep learning approaches for fintech sentiment analysis. This paper additionally summarizes deep learning methods, their advantages and disadvantages, and recent challenges associated with sentiment analysis in fintech.
引用
收藏
页码:118 / 122
页数:5
相关论文
共 27 条
[1]   Enhancing the Prediction of Stock Market Movement Using Neutrosophic-Logic-Based Sentiment Analysis [J].
Abdelfattah, Bassant A. ;
Darwish, Saad M. ;
Elkaffas, Saleh M. .
JOURNAL OF THEORETICAL AND APPLIED ELECTRONIC COMMERCE RESEARCH, 2024, 19 (01) :116-134
[2]  
Ahmadi S., 2024, International Journal of Current Science Research and Review, V7
[3]  
Al Ryan A, 2023, INT C COMP INT DAT S, P126
[4]  
AlSaqqa Samar, 2019, AIRC 19
[5]  
[Anonymous], 2020, HOW DOES LEARNING RATE DECAY HELP MODERN NEURAL NETWORKS?
[6]  
B. S, 2020, Binary Image classifier CNN using TensorFlow-TechiepediaMedium
[7]  
Chen CC, 2020, Arxiv, DOI arXiv:2005.01320
[8]   Prediction of the Stock Market From Linguistic Phrases: A Deep Neural Network Approach [J].
Eachempati, Prajwal ;
Srivastava, Praveen Ranjan .
JOURNAL OF DATABASE MANAGEMENT, 2023, 34 (01)
[9]  
Gholamalinezhad H, 2020, Arxiv, DOI arXiv:2009.07485
[10]   Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers [J].
Hohman, Fred ;
Kahng, Minsuk ;
Pienta, Robert ;
Chau, Duen Horng .
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2019, 25 (08) :2674-2693