Jebakumar D Immanuel, Harish M Ragavan, Priscilla G Rani, K. Niveditaa, G. Manikandan
{"title":"人工智能检测社交媒体用户的抑郁极性得分","authors":"Jebakumar D Immanuel, Harish M Ragavan, Priscilla G Rani, K. Niveditaa, G. Manikandan","doi":"10.1109/ICSCDS53736.2022.9761007","DOIUrl":null,"url":null,"abstract":"The main cause of disability and suicide is depression, which contributes most to global disability. Face-to-face interviews are typically used by psychologists to diagnose depressed individuals. The use of social media as a means of expressing one's mood has grown in recent years. A person's polarity influences how their emotions and opinions are analysed in Sentiment Analysis (SA). There is an implicit or explicit expression of sentiment in the text. Numerous studies on mental depression found that tweets created by users with major mental disturbances are used for depression detection. To aid the process of depression detection, this research study leverages social media (Twitter) data to forecast depressed users and estimate their depression intensity. LSTMs that are lexicon-enhanced are generally recommended. A lexicon-enhanced, deep learning-based LS TM model was proposed.","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"AI to Detect Social Media users Depression Polarity Score\",\"authors\":\"Jebakumar D Immanuel, Harish M Ragavan, Priscilla G Rani, K. Niveditaa, G. Manikandan\",\"doi\":\"10.1109/ICSCDS53736.2022.9761007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The main cause of disability and suicide is depression, which contributes most to global disability. Face-to-face interviews are typically used by psychologists to diagnose depressed individuals. The use of social media as a means of expressing one's mood has grown in recent years. A person's polarity influences how their emotions and opinions are analysed in Sentiment Analysis (SA). There is an implicit or explicit expression of sentiment in the text. Numerous studies on mental depression found that tweets created by users with major mental disturbances are used for depression detection. To aid the process of depression detection, this research study leverages social media (Twitter) data to forecast depressed users and estimate their depression intensity. LSTMs that are lexicon-enhanced are generally recommended. A lexicon-enhanced, deep learning-based LS TM model was proposed.\",\"PeriodicalId\":433549,\"journal\":{\"name\":\"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)\",\"volume\":\"2012 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSCDS53736.2022.9761007\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSCDS53736.2022.9761007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
AI to Detect Social Media users Depression Polarity Score
The main cause of disability and suicide is depression, which contributes most to global disability. Face-to-face interviews are typically used by psychologists to diagnose depressed individuals. The use of social media as a means of expressing one's mood has grown in recent years. A person's polarity influences how their emotions and opinions are analysed in Sentiment Analysis (SA). There is an implicit or explicit expression of sentiment in the text. Numerous studies on mental depression found that tweets created by users with major mental disturbances are used for depression detection. To aid the process of depression detection, this research study leverages social media (Twitter) data to forecast depressed users and estimate their depression intensity. LSTMs that are lexicon-enhanced are generally recommended. A lexicon-enhanced, deep learning-based LS TM model was proposed.