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  Published Paper Details:

  Paper Title

Twitter Tweets Suicidal Ideation Detection Using Deep Learning

  Authors

  Sai Deepthi Nagisetti,  Movva Hema Latha,  Kalluri Deepthi,  Guttula Krupa Harika

  Keywords

Deep Learning, LSTM (Long Short-Term Memory),CNN(Convolutional Neural Network),GRU(Gated Recurrent Unit).

  Abstract


The rise in technological advancements and Social Networking Sites (SNS) made people more engaged in their virtual lives. Research has revealed that people feel more comfortable posting their feelings, including suicidal thoughts, on SNS than discussing them through face-to-face settings due to the social stigma associated with mental health .Many suicidal deaths can be prevented by understanding how people communicate their distress related thoughts. Early understanding of the risk factors and warning signs can decrease the threshold for suicide and help prevent many deaths. This Project aims to develop a system that can detect suicidal ideation on Twitter tweets using DL models. In this project we trained several Deep learning models such as LSTM, GRU, and CNN.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2311028

  Paper ID - 245722

  Page Number(s) - a205-a213

  Pubished in - Volume 11 | Issue 11 | November 2023

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Sai Deepthi Nagisetti,  Movva Hema Latha,  Kalluri Deepthi,  Guttula Krupa Harika,   "Twitter Tweets Suicidal Ideation Detection Using Deep Learning", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 11, pp.a205-a213, November 2023, Available at :http://www.ijcrt.org/papers/IJCRT2311028.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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