Abstract
Mental health conditions are one thing that needs to be considered as important as physical health. Depression is a mental disorder that can affect a person's social life. The Twitter social media platform is where users can pour their hearts out in the form of tweets. This is often the background of a person's level of depression. Accessible and diverse interactions on Twitter considerably influence the psychological condition of its users. This study aims to detect the level of depression through data obtained from Twitter social media tweets. The method used is RoBERTa which is an optimized BERT retraining. Several scenarios are used to get the best accuracy results in text classification. To get the evaluation results, it is necessary to measure using the Confusion Matrix method. The accuracy value is 72% based on numerous tests that have been done.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
