A Comprehensive Review of Investor Sentiment Analysis in Stock Price Forecasting

Resource type
Authors/contributors
Title
A Comprehensive Review of Investor Sentiment Analysis in Stock Price Forecasting
Abstract
Sentiment analysis technologies have a strong impact on financial markets. In recent years there has been increasing interest in analyzing the sentiment of investors. The objective of this paper is to evaluate the current state of the art and synthesize the published literature related to the financial sentiment analysis, especially in investor sentiment for prediction of stock price. Starting from this overview the paper provides answers to the questions about how and to what extent research on investor sentiment analysis and stock price trend forecasting in the financial markets has developed and which tools are used for these purposes remains largely unexplored. This paper represents the comprehensive literature-based study on the fields of the investors sentiment analytics and machine learning applied to analyzing the sentiment of investors and its influencing stock market and predicting stock price.
Date
2021-10
Proceedings Title
2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)
Conference Name
2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)
Pages
264-268
Library Catalog
IEEE Xplore
Citation
Ma, H., Ma, J., Wang, H., Li, P., & Du, W. (2021). A Comprehensive Review of Investor Sentiment Analysis in Stock Price Forecasting. 2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall), 264–268. https://doi.org/10.1109/ICISFall51598.2021.9627470