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@article{151667,
        author = {Janhavi Deokar and Radhika Baheti and Gauri Shirkande and Sneha Bodake and Archana. K},
        title = {Stock Market Analysis from Social Media and News using Machine Learning Techniques},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {478-483},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151667},
        abstract = {Stock market analysis and prediction is a major factor of profit and growth for investors in the business of any field. Investors check the performance of a company before deciding to purchase its stock, to avoid buying stocks which can be risky. Prediction plays an important role in the business of the stock market which is a very complicated and challenging process. Correct prediction of stocks can lead to huge profits for the sellers and the brokers. Prediction of stocks can be done by carefully analyzing the history of the respective stock market. In this paper, we use different machine learning algorithms on social media and financial news data for stock prediction. We can perform feature selection and spam tweets reduction to improve performance and quality of prediction. Random forest classifiers are found to be more consistent and accurate.},
        keywords = {Feature selection, Forest Classifier, Machine Learning, Random, Sentiment analysis, Stock market prediction},
        month = {},
        }