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Journal: International Journal of Advanced Research in Engineering and Technology (IJARET) (Vol.11, No. 11)

Publication Date:

Authors : ;

Page : 1123-1130

Keywords : Machine Learning; Prediction; Sentiment Analysis; Twitter API.;

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In recent years, the generation of user data has greatly increased. Due to the development of Internet-based applications, social media users have grown exponentially. Millions of users share their opinions every day. Therefore, social media has become a powerful communication tool and a rich source of opinion data. This data is usually used to influence a large number of people. Over the years, this process has gained momentum and led to the development of a new era of research, namely sentiment analysis. Sentiment analysis (also known as opinion mining) uses new technologies and algorithms to collect and analyze opinions about various products and services. The main goal of this article is to use sentiment analysis and machine learning to predict stock prices. This feature can help investors predict the stock market. It may not be possible to accurately predict the stock market based on historical price analysis alone. In order to improve the prediction, we perform sentiment analysis based on the opinions of different Twitter users and add sentiment scores and prices. Although forecasting the stock market is a tedious task, there are many forecasting methods. By using the tensor flow platform and Twitter API to get tweets, we have implemented a new sentiment analysis method. Our results show that this scheme has better accuracy than existing methods in predicting the stock market.

Last modified: 2021-02-22 19:40:10