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Paper Title : Sentiment Classification of Financial Texts for Stock Markets using LSTM Technique: A Survey

ISSN : 2395-1303
Year of Publication : 2022
10.5281/zenodo.7556442

Authors: Kanchan Raipure, Prof. Mahendra Sahare, Prof. Anurag Shrivastava

         


Abstract
Sentiment Analysis (SA) is the current field of research in text mining field. SA is detecting opinions, sentiments, and subjectivity of text. It is the application of natural language processing techniques and text analytics to identify and extract subjective information from the frequently used sources such as web and microblogs. The main objective of sentiment analysis is to analyze reviews of products and services, and determine the scores of such sentiments. The major problem is that the reviews are mostly unstructured and thus, need classification or clustering to provide meaningful information for future use. The study was conducted with different sectors like, IT sector, Automobile sector, Banking sector, Pharmaceutical sector and FMCG sector. All the sectors taken for the study is highly volatile compared to other sectors in NSE/BSE. Hence it is very essential to study on the nexus between the Indian Stock Market and selected companies behavior. The early stage of the share market was very familiar for average investor. Now the markets are wide enough to invest. There are different markets like bond market, forex market, derivative market and other specialty markets. Analysis of the stock price we take the price. By using the artificial neural network, we develop a model. within the neural network, we use a recurrent neural network that remembers each and each information through time.

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Keywords
— National Stock Exchange (NSE), Bombay Stock Exchange (BSE), Neural Network