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  1. Home
  2. Academic Research Output
  3. Conference Paper
  4. A Comprehensive Review of Investor Sentiment Analysis in Stock Price Forecasting
 
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A Comprehensive Review of Investor Sentiment Analysis in Stock Price Forecasting

Date Issued
2021
Author(s)
Ma, Huawen
Ma, Jixin
Wang, Han
Li, Pengsheng
Du, George 
Institute for Data Engineering and Science 
DOI
10.1109/ICISFall51598.2021.9627470
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.
Subjects

Social media

Machine learning

Information science

Market research

Analytical models

Predictive models

Sentiment analysis

Investor sentiment an...

Reliability

Stock price trend for...

Tools

File(s)
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Name

Waiting for Repository Version.pdf

Size

37.66 KB

Format

Adobe PDF

Checksum

(MD5):70439f9ac5a8bde2f366653765cefe3c


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