%0 Journal Article %1 noauthororeditor %A A, Rahul Kumar Sharma | Vijayakumar %D 2021 %J International Journal of Trend in Scientific Research and Development %K (NLTK) Depression Flask Health Language Mental Natural Toolkit Twitter Wordcloud %N 4 %P 724-727 %T Depression Detection in Tweets using Logistic Regression Model %U https://www.ijtsrd.comcomputer-science/data-miining/41284/depression-detection-in-tweets-using-logistic-regression-model/rahul-kumar-sharma %V 5 %X In the growing world of modernization, mental health issues like depression, anxiety and stress are very normal among people and social media like Facebook, Instagram and Twitter have boosted the growth of such mental health. Everything has its legitimacy and negative mark. During this pandemic, people are more likely to suffer from mental health issues, they are available 24 7 and are cut off from the real world. Past examinations have shown that individuals who invest more energy via online media are bound to be depressed. In this project, we find out people who are depressed based on their tweets, followers, following and many other factors. For this, I have trained and tested our text classifier, which will distinguish between the user who is depressed or not depressed. Rahul Kumar Sharma | Vijayakumar A "Depression Detection in Tweets using Logistic Regression Model" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41284.pdf Paper URL: https://www.ijtsrd.comcomputer-science/data-miining/41284/depression-detection-in-tweets-using-logistic-regression-model/rahul-kumar-sharma

@article{noauthororeditor, abstract = {In the growing world of modernization, mental health issues like depression, anxiety and stress are very normal among people and social media like Facebook, Instagram and Twitter have boosted the growth of such mental health. Everything has its legitimacy and negative mark. During this pandemic, people are more likely to suffer from mental health issues, they are available 24 7 and are cut off from the real world. Past examinations have shown that individuals who invest more energy via online media are bound to be depressed. In this project, we find out people who are depressed based on their tweets, followers, following and many other factors. For this, I have trained and tested our text classifier, which will distinguish between the user who is depressed or not depressed. Rahul Kumar Sharma | Vijayakumar A "Depression Detection in Tweets using Logistic Regression Model" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41284.pdf Paper URL: https://www.ijtsrd.comcomputer-science/data-miining/41284/depression-detection-in-tweets-using-logistic-regression-model/rahul-kumar-sharma }, added-at = {2021-07-15T10:03:40.000+0200}, author = {A, Rahul Kumar Sharma | Vijayakumar}, biburl = {https://www.bibsonomy.org/bibtex/24388474ea020b1035e935b9a5e432008/ijtsrd}, interhash = {8109da5d92ab484c40c84afdd5adeca8}, intrahash = {4388474ea020b1035e935b9a5e432008}, issn = {2456-6470}, journal = {International Journal of Trend in Scientific Research and Development}, keywords = {(NLTK) Depression Flask Health Language Mental Natural Toolkit Twitter Wordcloud}, language = {english}, month = jun, number = 4, pages = {724-727}, timestamp = {2021-07-15T10:03:40.000+0200}, title = {Depression Detection in Tweets using Logistic Regression Model }, url = {https://www.ijtsrd.comcomputer-science/data-miining/41284/depression-detection-in-tweets-using-logistic-regression-model/rahul-kumar-sharma}, volume = 5, year = 2021 }