Abstract:
Depression is a serious conditioned mental disorder that has significant
effects on the quality of life of a person. Internet sources state that the number of
people suffering from depression is getting increased day by day and it affects
teenagers more than adults. Our project in this work is to find the status
of a user's posts or comments which show depression mood or not, using
different types of machine learning classification algorithms. The dataset is
collected from users who share their day-to-day status on social networks. The
dataset is preprocessed and tokenized to make it compatible to feed into
different types of algorithms such as Naïve Bayes, Random Forest, Linear
Regression, and Support Vector Machine. During the process, the accuracy level of
each algorithm is compared and the algorithm with the highest accuracy has
chosen as suitable to process further prediction.
