Machine learning based forecasting for analyzing correlation between social attention and study abroad trend for Pakistani students

Abstract

We exist in a digital world where even small information is shared and discussed on social media from every part of the world. Social media have great impact on individual learning and play a role in one's decision making. In this paper, we have employed machine learning and pattern classification algorithms to see whether there exists any correlation between social media online discussion forums and people's browsing behavior. We have analyzed and proposed a new casting (predicting) model to understand the correlation between social attention and study abroad trend among Pakistani students. Analysis has been carried out with the three different parameters that include Tendency, Seasonality, and Correlation between the Google Trend tool and online discussion forums for students about the general information of studying abroad in different countries for availing different Scholarships. Correlation analysis identifies the degree of relationship or dependency between these two variables. Proposed work offers novel point of view in the area of data mining and machine learning to investigate and predict the relationship between study-abroad tend and browsing behavior of Pakistani students.