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- Title
A Study of Stock Market Prediction through Sentiment Analysis.
- Authors
Biswas, Sandipan; Ghosh, Shivnath; Roy, Sandip; Bose, Rajesh; Soni, Sanjay
- Abstract
In the modern world, the current state and course of economic development and growth are determined by the fortunes and vagaries of the stock markets. In this research study, the authors provide a model that can aid in making reliable and error-free predictions of stock market trends. The research's described approach uses sentiment analytics based on financial news and past stock market patterns. The suggested model can provide more accurate results because it examines information from numerous news sources as well as the history of price development of specific equities. The proposed structure has been used to forecast stock market patterns that incorporate sentiment analysis taken from news and previous stock market patterns to provide more precise results from a variety of news data and the history of the price up and down of specific equities. The model shown here has provided a two-step process. The Naive Bayes algorithm has been utilized in the initial step to assess text polarity and determine the general mood of news data gathered and received. The next stage involves forecasting future values of stocks using evaluation findings on text polarity and historical stock value movement information. A novel idea known as the KNN-LR Hybrid algorithm has been introduced to achieve better outcomes when evaluating the accuracy and efficacy of other machine learning algorithms.
- Subjects
SENTIMENT analysis; STOCK exchanges; ECONOMIC development; NAIVE Bayes classification; LOGISTIC regression analysis; BSE Ltd.
- Publication
Mapana Journal of Sciences, 2023, Vol 22, Issue 1, p89
- ISSN
0975-3303
- Publication type
Article
- DOI
10.12723/mjs.64.6