Abstract:
Coronavirus outbreaks have had a Signiant impact on human life. This thesis considers the
detection of depression by applying a system that can effectively detected depressing text
from various post in covid situation. The pandemic has an indirect effect on human mental
health, which is irreversible but difficult to assess. One of the most frequent mental ailments
is depression. More than 300 million individuals are said to be depressed over the world.
This equates to about 4.4 percent of the global population. Facebook is great platform for
people to express their emotions. We focused on the depressing post obtained from
Facebook and how many individuals reacted to them in this article. We build the dataset
for the training purpose by manually labelling 1000 Bengali and 1000 English Facebook
post. In this study, we use machine learning algorithm, which has over-performing aspect
on my classifications and a method weighing input properties implies on their
importance.to classify our data and notice greater accuracy, we applied python and several
common machine learning approaches.
