Data-Driven Analysis of Mental Health Trends Using Social Media and Public Survey Data

@article{1709632,
      author = {Manav Doshi},
      title = {Data-Driven Analysis of Mental Health Trends Using Social Media and Public Survey Data},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {1},
      pages = {570-573},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1709632.pdf},
      abstract = {This research paper presents a comprehensive data analysis of mental health trends using social media platforms and publicly available survey datasets. The study leverages sentiment analysis and natural language processing techniques to evaluate public discourse around mental health-related keywords. By integrating insights from social media text and formal survey data, the project identifies common emotional patterns, peak periods of distress, and demographic distributions of mental health concerns. The findings emphasize the importance of early detection, policy intervention, and public awareness.},
      keywords = {Mental Health, Sentiment Analysis, Social Media, Survey Data, Data Mining, NLP, Public Health Trends.},
      month = {July},
  }