An Intelligent and Social-Oriented Sentiment Analytical Model for Stock Market Prediction using Machine Learning and Big Data Analysis

Muqing Bai, Yu Sun
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Abstract

In an era of machine learning, many fields outside of computer science have implemented machine learning as a tool [5]. In the financial world, a variety of machine learning models are used to predict the future prices of a stock in order to optimize profit. This paper preposes a stock prediction algorithm that focuses on the correlation between the price of a stock and its public sentiments shown on social media [6].We trained different machine learning algorithms to find the best model at predicting stock prices given its sentiment. And for the public to access this model, a web-based server and a mobile application is created. We used Thunkable, a powerful no code platform, to produce our mobile application [7]. It allows anyone to check the predictions of stocks, helping people with their investment decisions.
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基于机器学习和大数据分析的股票市场预测智能和面向社会的情绪分析模型
在金融领域,各种各样的机器学习模型被用来预测股票的未来价格,以优化利润。本文提出了一种股票预测算法,主要关注社交媒体上的股票价格与公众情绪之间的相关性[6]。我们训练了不同的机器学习算法,以找到预测股票价格的最佳模型。为了让公众访问这个模型,我们创建了一个基于web的服务器和一个移动应用程序。我们使用了Thunkable(一个强大的无代码平台)来制作我们的移动应用程序[7]。它允许任何人查看股票预测,帮助人们做出投资决策。
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