Stock-Market-Sentiment-Analysis
gandalf1819
Identification of trends in the stock prices of a company by performing fundamental analysis of the company. News articles were provided as training data-sets to the model which classified the articles as positive or neutral. Sentiment score was computed by calculating the difference between positive and negative words present in the news article. Comparisons were made between the actual stock prices and the sentiment scores. Naive Bayes, OneR and Random Forest algorithms were used to observe the results of the model using Weka
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7 data points · 2021-08-01 → 2025-03-01How do you feel about this project?
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Question copied to clipboardWhat is the gandalf1819/Stock-Market-Sentiment-Analysis GitHub project? Description: "Identification of trends in the stock prices of a company by performing fundamental analysis of the company. News articles were provided as training data-sets to the model which classified the articles as positive or neutral. Sentiment score was computed by calculating the difference between positive and negative words present in the news article. Comparisons were made between the actual stock prices and the sentiment scores. Naive Bayes, OneR and Random Forest algorithms were used to observe the results of the model using Weka". Written in R. Explain what it does, its main use cases, key features, and who would benefit from using it.
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