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The analysis of data and information is critical, and for stock market traders or investors this can be very crucial. Especially with the progress the world has seen with technology in recent years, as these improvement and changes may come to affect how people perceive things and how they take decision. In this paper we are going to use two methods to classify tweets of Tesla stock that ranges from 30-09-2021 to 30-09-2022, preprocess the features along with financial data from Yahoo Finance to predict close price of the following day using LSTM. Therefore comparing the price prediction models resulted from each method of sentiment analysis, and observing the role of sentiment extraction models in determining the accuracy of price prediction models.

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Using Sentiment Analysis Extracted Features to Predict Stock Price

  • 会议论文

  • 发表日期：

    2026年

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  • Mariame Tarsi,
  • Ibtissame Ezzahoui,
  • Samira Douzi,
  • Abdelaziz Marzak

摘要

The analysis of data and information is critical, and for stock market traders or investors this can be very crucial. Especially with the progress the world has seen with technology in recent years, as these improvement and changes may come to affect how people perceive things and how they take decision. In this paper we are going to use two methods to classify tweets of Tesla stock that ranges from 30-09-2021 to 30-09-2022, preprocess the features along with financial data from Yahoo Finance to predict close price of the following day using LSTM. Therefore comparing the price prediction models resulted from each method of sentiment analysis, and observing the role of sentiment extraction models in determining the accuracy of price prediction models.