scholarly journals Predicting Stock Market Behavior using Data Mining Technique and News Sentiment Analysis

Author(s):  
Ayman E. Khedr ◽  
◽  
S.E.Salama ◽  
Nagwa Yaseen
Author(s):  
Zubair Akbar

The pandemic of Covid-19 which started in the year 2019 did not just cause an effect on the living of millions of people but in the economic and social sectors of every part of the world as well. It is a challenging task to determine the interrelation between COVID-19 cases concerning the economy in the top affected countries. This paper explores; how severe Impact of COVID-19 1st wave on the economic facets of Pakistan as compared to the Top Fifteen affected countries. Moreover, this paper uses COVID-19 well-known dataset provided by John Hopkins and Stock Market Datasets collectively to carry out the critical analysis successfully. We found a relationship between the cumulative numbers of confirmed cases in each country with a declining state of countries' economies: the higher decline in the stock market indicates a higher number of confirmed cases.


2015 ◽  
Vol 21 (2) ◽  
pp. 95
Author(s):  
Hyo Soung Cha ◽  
Tae Sik Yoon ◽  
Ki Chung Ryu ◽  
Il Won Shin ◽  
Yang Hyo Choe ◽  
...  

2016 ◽  
Vol 139 (6) ◽  
pp. 46-47
Author(s):  
M. Ashrafa ◽  
D. Asha ◽  
D. Radha ◽  
M. Sangeetha ◽  
R. Jayaparvathy

Author(s):  
Mr. Bhushan Bandre, Ms. Rashmi Khalatkar

Major decision making process using large amount of data can be done by various techniques using data mining. In education sectors various data mining techniques are implemented to analyze the student’s data from the admission process itself. Due to large number of educational institution in India, excellence becomes a major parameter for the institutions to grow and with stand. Nowadays education institutions use data mining techniques to show their excellence. The main objective of this work to present an analysis of individual semester wise results of engineering college students using different techniques of data mining. Here we used different classification algorithms like decision tree, rule based, function based and Bayesian algorithms to analyze the semester results and comparison is made by considering parameters like accuracy and error rate. Our output shows the most suited algorithm for analyzing data in educational institutions.


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