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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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The rates of diagnosing depression and mental illness during the last few decapods, a number of cases prevail unheard-of.Symptoms linked to mental illness are detectable on Twitter, Facebook and web forums and au-tomatic methods are more and more able to locate inactivi-ty and other mental disease. In this project, latest studies that planned to detect depression and mental illness by the use of social media are surveyed. Mentally ill users have already been pointed out the use of screening surveys, their community distribution of analysis on twitter, or by their membership in online forums, and that they were detectable originating at regulate users be patterns in their language and online activity. Various automateddetection methods can help to detect depressed people using social media. In addition a number of authors experience that various Social Networking Sites activities may be linked to low self-confidence, particularly in young people and adolescents. In our project the mental disorder is predicted by algorithms namely K-Means Nearest Neighbor (KNN) and Deep Belief Network (DBN). We can prove that DBN works better than other algorithms in terms of accuracy.
Keywords:
Deep Belief Network (DBN, restricted Boltzmann ma-chines,KNN algorithms
Cite Article:
"PREDICTING ONLINE GAME DISORDER CAUSED IN YOUNGSTERS", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 5, page no.747 - 749, May-2023, Available :http://www.ijsdr.org/papers/IJSDR2305112.pdf
Downloads:
000222060
Publication Details:
Published Paper ID: IJSDR2305112
Registration ID:206292
Published In: Volume 8 Issue 5, May-2023
DOI (Digital Object Identifier):
Page No: 747 - 749
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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