Impact of Social Media Affecting Student's Academic Performance using Opinion Mining

In this modern world, social media network plays a major role and impact student community. Mostly, students are influenced by social media. This study focuses on how social media affects the age group such as 18–21 years and how smartphones are affecting their health, education, family, society, and what are steps should be taken by institutions, family, society to overcome students' problems. Till now, many researches have focused only on the classification of numeric data. In order to overcome the problems of classification and regression, the Decision tree Classifier and logistics regression method are combined as voting non-ensemble models for analyzing non-numeric data. In our work, the opinion mining technique uses a natural language process and computational semantics to extract and identify opinion or sentiment within the specified text. The main aim of this study is to investigate the behavioral changes of the students due to social media such as Facebook, Twitter, and WhatsApp. The result determines that there is a significant association between the time spent on social media and academic performance. This paper attempts to analyze the academic-related non-numeric data and check for the aspects of positive or negative feedback.