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Social media data analysis to predict mental state of users using machine learning techniques.

R Lokeshkumar1, Om Ashish Mishra1, Shivam Kalra1

  • 1Department of Analytics, Vellore Institute of Technology, Vellore, Tamil Nadu, India.

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Social media use is linked to increased road accidents, murders, and suicides in India. This study analyzes social media data to understand its impact on societal issues and raise awareness among the youth.

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Area of Science:

  • Social Sciences
  • Computer Science
  • Public Health

Background:

  • Social media platforms (e.g., Facebook, WhatsApp, Instagram) are increasingly popular across all age groups.
  • The mental state of individuals on social media platforms remains largely unknown.
  • This research investigates the influence of social media on critical social issues including road accidents, murders, and suicides.

Purpose of the Study:

  • To analyze the impact of social media on societal issues in India.
  • To predict mental states and understand public sentiment related to sensitive topics.
  • To provide real-world solutions for social advancement through data analysis.

Main Methods:

  • Utilized Google Forms for data collection.
  • Employed machine learning algorithms for predictive analysis.
  • Conducted sentiment analysis on Twitter data to gauge public opinion.
  • All datasets were India-specific.

Main Results:

  • Static and dynamic data analysis revealed various sentiment trends and predictions.
  • Identified techniques for predicting different mental states.
  • The findings highlight the growing prevalence of social issues linked to online behavior.

Conclusions:

  • The study clearly demonstrates the connection between social media engagement and involvement in social issues such as murder, road accidents, and suicide.
  • Research findings enhance understanding of youth sensitivity and promote social awareness.
  • Emphasizes the need for greater awareness regarding the societal impact of social media.