Mental health detection by using Natural Language Processing and Machine Learning on social networks

نوع: Type: thesis

مقطع: Segment: masters

عنوان: Title: Mental health detection by using Natural Language Processing and Machine Learning on social networks

ارائه دهنده: Provider: Hamidreza Safari

اساتید راهنما: Supervisors: Dr Mansuri zadeh - Dr Nasiri

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: Dr.Khotanlu - Dr.Dezfulian

زمان و تاریخ ارائه: Time and date of presentation: 2021

مکان ارائه: Place of presentation: room 4

چکیده: Abstract: During this unprecedented time when the world is suffering from coronary heart disease, the number of people suffering from mental illness has increased for various reasons, including social distance, unemployment, stress, and the like. In addition, depression is one of the most common illnesses worldwide, which according to the World Health Organization estimates that more than 8% of the world's population suffers from it. Necessary treatments have been provided. Past results and research show the potential of social media in diagnosing mental illness. The aim of this dissertation is to introduce a deep learning model with natural language processing methods that can identify the opinions of people with mental illness based on the content produced. To achieve this goal, we have taught a classifier using a torsional neural network that can Diagnose diseases more accurately than previous models. It should also be noted that measuring the severity of mental illness is a difficult task that only a specialist can achieve using a variety of techniques and methods; Therefore, textual diagnosis of mental illness can be used as a preliminary step solely to raise awareness

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