Informatics Publishing Limited

Kalyani Joshi ¹, H. N. Bharathi ¹, Jyothi Rao ¹

Affiliations
1 Department of Computer Engineering, K. J. Somaiya College of Engineering, Mumbai, IN

Abstract

Efficient Market Hypothesis is the popular theory about stock prediction. With its failure much research has been carried in the area of prediction of stocks. This project is about taking non quantifiable data such as financial news articles about a company and predicting its future stock trend with news sentiment classification. Assuming that news articles have impact on stock market, this is an attempt to study relationship between news and stock trend. To show this, we created three different classification models which depict polarity of news articles being positive or negative. Observations show that RF and SVM perform well in all types of testing. Naïve Bayes gives good result but not compared to the other two. Experiments are conducted to evaluate various aspects of the proposed model and encouraging results are obtained in all of the experiments. The accuracy of the prediction model is more than 80% and in comparison with news random labelling with 50% of accuracy; the model has increased the accuracy by 30%.

Keywords

Text Mining, Sentiment Analysis, Naive Bayes, Random forest, SVM, Stock Trends.

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Sudha Gupta ¹, Ravindra Salvi ², Deepak Sharma ³, Sonali Patil ⁴, H. N. Bharathi ³, Swati Mahajan ⁵, Manoj Palsodkar ⁶

Affiliations
1 Department of Electronics Engineering, KJ Somaiya College of Engineering, Vidyavihar, Mumbai, IN
2 Department of Science and Humanities, KJ Somaiya College of Engineering, Vidyavihar, Mumbai, IN
3 Dept. of Computer Engg., KJ Somaiya College of Engineering, Vidyavihar, Mumbai, IN
4 Dept. of Information Technology, KJ Somaiya College of Engineering, Vidyavihar, Mumbai, IN
5 Dept. of Electronics and Telecommunication Engg., KJ Somaiya College of Engineering, Vidyavihar, Mumbai, IN
6 Dept. of Mechanical Engineering, KJ Somaiya College of Engineering, Vidyavihar, Mumbai, IN

Abstract

The fee structure of many self-financed colleges in India may be exorbitant to aspiring students coming from the financially weaker section. The problem is even more pertinent when staying cost gets added for outside Mumbai students. The paper aims to focus on the process of building a mechanism to bring technical education within reach of the financially needy students, who are admitted to K.J. Somaiya College of Engineering Mumbai (KJSCE). With an aim of raising funds to support such needy students, employees of KJSCE came together and extended a helping hand to establish an organization named as "PUSH" (People United for Students' Help). This paper describes the functioning of PUSH-KJSCE and its long-lasting impact on the lives of low-income students. PUSH-KJSCE, a management-inspired practice in KJSCE, ensured an economic support system as well as much-needed facilities to financially weaker students. As a result of this, it not only makes the students confident, but it also helps them to fulfil their dreams to become professionally qualified. The PUSH KJSCE is a success story of the best management practices which spread the rays of hope in the lives of young minds, such that they are no more hindered by financial obstacles and it also creates awareness in them to contribute and make this model sustainable.

Keywords

PUSH-KJSCE (People United for Students Help-K.J. Somaiya College of Engineering), Need Base Scholarship, Statistical Analysis, Students Feedback, Sustainable System.

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