Twitter is a social media application where liberty expression exists, no one can control what other people think and many of us share ideas. In 2022 mental health disease has increase a lot, as I mentioned before twitter is the safest place to hide (specially when you a teenager) where people don’t feel judged and common ideas are shared. This could be a great indicator to analyze data and identify what are the factors that lead this generation to mental diseases.
Analyzing twitter data as a tool to identify mental disease and inform the specialists, to help people and prevent conducts caused by mental disease.
The experiment starts with identifying a group of people based on specific age range 16-23 years making survey including basic questions of twitter usage. This is going to help us understand how users interact on twitter and if they feel related to other people emotions and feelings.
Based on people answers we are going to start looking for specific keywords related to emotions and analyze the statics based on tweets per hour related to that topics. Based on results a personal chatbot can be build offering users a list of specialists that offer the first therapy session for free and the next ones with a low cost. The idea is to offer at first free help to the user but as a friendly way, not making it seem as an ad.
We validate the hypotesis based on the survey results because most of the people feel related to other user tweets, but most of the users just read the content and don’t write about the way they feel on twitter. If we use this data to analyze user feelings based also on their interactions like retweets or likes we can have a better approach.
Mental diseases can be related based on user interaction via Twitter but is important to know this doesn’t guarantee that a user can have a diseases based on his data, because sometimes it can just be a bad day and in that case we shouldn’t worry.
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