Stock-Market-Sentiment-Analysis

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 (by gandalf1819)

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1
90
10.0
over 3 years ago

gandalf1819/Stock-Market-Sentiment-Analysis is an open source project licensed under GNU General Public License v3.0 only which is an OSI approved license.

The primary programming language of Stock-Market-Sentiment-Analysis is R.


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