Empirical Study of the Correlation between Social Media Content and Health Issues among College Students Using Machine Learning

This study analyzes the effect of social media content on college student addiction using data science techniques. It aims to examine the correlation between different types of social media content and addictive behavior in college students. The research methodology used is non-probability sampling with a sample size of 587 college students in Tamil Nadu, India. The study uses statistical tools such as correlation analysis, regression analysis, one-way ANOVA, and Friedman ranking test to analyze the data collected. The findings suggest that the factors influencing social media addiction are positively correlated with the health issues faced by college students. The study indicates that demographic variables such as age, gender, year in college, and place of living may play a role in shaping an individual's perception of social media addiction. The results of the study can inform the development of interventions and prevention strategies to reduce social media addiction among college students. The study recommends a multi-pronged approach to address the root causes of addiction and provide students with the tools and resources they need to manage their social media use and promote their physical and mental health.

Authors

Publication Details

Journal
Journal of Applied Data Sciences
Published
2024-12-01
DOI
https://doi.org/10.47738/jads.v5i4.365
Citations
1
Primary Topic
Mental Health via Writing
Type
article
Field-Weighted Citation Impact
0.64
Controls
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article

Empirical Study of the Correlation between Social Media Content and Health Issues among College Students Using Machine Learning

M. Hemalatha
1 citations
Journal of Applied Data Sciences
Mental Health via Writing
0.64
article

Empirical Study of the Correlation between Social Media Content and Health Issues among College Students Using Machine Learning

M. Hemalatha
article en
1 citations

Abstract

This study analyzes the effect of social media content on college student addiction using data science techniques. It aims to examine the correlation between different types of social media content and addictive behavior in college students. The research methodology used is non-probability sampling with a sample size of 587 college students in Tamil Nadu, India. The study uses statistical tools such as correlation analysis, regression analysis, one-way ANOVA, and Friedman ranking test to analyze the data collected. The findings suggest that the factors influencing social media addiction are positively correlated with the health issues faced by college students. The study indicates that demographic variables such as age, gender, year in college, and place of living may play a role in shaping an individual's perception of social media addiction. The results of the study can inform the development of interventions and prevention strategies to reduce social media addiction among college students. The study recommends a multi-pronged approach to address the root causes of addiction and provide students with the tools and resources they need to manage their social media use and promote their physical and mental health.

Journal of Applied Data SciencesVol. 5(4)
Quality Education
Openalex Percentile: Top 25%
Mental Health via Writing
0.64
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