Detection of Suicidal Ideation in Social Media Through Content Analysis

Authors

  • K. Divya Assistant Professor, Department of CSE-AI & ML, Sri Vasavi Institute of Engineering & Technology, Nandamuru, Andhra Pradesh, India Author
  • Kona Namratha Blessy UG Student, Department of CSE-AI & ML, Sri Vasavi Institute of Engineering & Technology, Nandamuru, Andhra Pradesh, India Author
  • Yarramsetty Lalasa Navya UG Student, Department of CSE-AI & ML, Sri Vasavi Institute of Engineering & Technology, Nandamuru, Andhra Pradesh, India Author
  • Jonnala Kumar Swamy UG Student, Department of CSE-AI & ML, Sri Vasavi Institute of Engineering & Technology, Nandamuru, Andhra Pradesh, India Author
  • Sammeta Manikanta UG Student, Department of CSE-AI & ML, Sri Vasavi Institute of Engineering & Technology, Nandamuru, Andhra Pradesh, India Author

Keywords:

Content Analysis, Social Networks, Neural Networks, Machine Learning, Groups of Death, Python

Abstract

This article describes content analysis of text with to identify suicidal tendencies and types. This article also describes how to make a sentence classifier that uses a neural network created using various libraries created for machine learning in the Python programming language. Attention is paid to the problem of teenage suicide and «groups of death» in social networks, the search for ways to stop the propaganda of suicide among minors. Analysis of existing information about so-called «groups of death» and its distribution on the Internet.

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References

Research group «Monitoring of current folklore. Groups of death — from play to moral panic. RANHiGS [RANEPA’s typography], 2017. (in Russian)

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Published

26-04-2024

Issue

Section

Research Articles

How to Cite

Detection of Suicidal Ideation in Social Media Through Content Analysis. (2024). International Journal of Scientific Research in Science and Technology, 11(2), 862-869. https://ijsrst.com/index.php/home/article/view/IJSRST24112147

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