A Deep Learning Model to Analyse Social-Cyber Psychological Problems in Youth  

作　　者：Ali Alqazzaz Mohammad Tabrez Quasim Mohammed Mujib Alshahrani Ibrahim Alrashdi Mohammad Ayoub Khan 

机构地区：[1]College of Computing and Information Technology,University of Bisha,67714,Bisha,Saudi Arabia [2]Department of Computer Science,College of Computer and Information Sciences,Jouf University,Sakaka,Aljouf,72388,Saudi Arabia

出　　处：《Computer Systems Science & Engineering》2023年第7期551-562,共12页计算机系统科学与工程（英文）

基　　金：This project was funded by Deanship of Scientific Research,University of Bisha,Bisha,Kingdom of Saudi Arabia.

摘　　要：Facebook,Twitter,Instagram,and other social media have emerged as excellent platforms for interacting with friends and expressing thoughts,posts,comments,images,and videos that express moods,sentiments,and feelings.With this,it has become possible to examine user thoughts and feelings in social network data to better understand their perspectives and attitudes.However,the analysis of depression based on social media has gained widespread acceptance worldwide,other verticals still have yet to be discovered.The depression analysis uses Twitter data from a publicly available web source in this work.To assess the accuracy of depression detection,long-short-term memory(LSTM)and convolution neural network(CNN)techniques were used.This method is both efficient and scalable.The simulation results have shown an accuracy of 86.23%,which is reasonable compared to existing methods.

关 键 词：Emotions DEPRESSION social media 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]