General Depression Detection Analysis Using IndoBERT Method

Abstract

Many of the tweets we discover on Twitter are concerning feelings of depression which will be caused by varied things. The amount of tweets additionally continues to increase. To be able to decide however depressed a user is, analysing tweets from users can facilitate with that. The method of analysing the detection of depression can help to supply applicable treatment for users who are detected to own depression. During this paper, the users to be analysed are users who have more than 1000 tweets and are Indonesian tweets. Then, crawling / retrieval of user tweet data is carried out. After that, data pre-processing is done. Once that done, using the IndoBERT method to classify the data obtained. In the end, this paper provides the accuracy value of this detection analysis using the IndoBERT method with an accuracy value of 51% and F1-Score of 31%.