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Now a days mental health disorders are a major problem. Anxiety, depression, bipolar illness, long-term stress, and various personality disorders are common conditions. Due to non availability and less access to physicians and other medical specialists, many issues go undetected. This method automatically determines whether a person is suffering from mental health issue is proposed in this research. To examine what people write and attempt to comprehend their behaviour, we employ a technique known as Support Vector Machines. The technique known as Term Frequency-Inverse Document Frequency to quantify what people write. I also employ a list of words that are related to emotions to obtain a better grasp of what individuals are writing. I used a corpus of texts from people to test our system. 52,680 writings were present. Iam able to identify the type of behaviour they represented because they were all labelled and attempted numerous approaches of training our system to acquire the best results. The suggested approach performed well in classification across all behaviour categories. Compared to the systems used in this purpose, this is superior. Addition to that this tool that can be used to assess individuals mental health issues instantly. Support Vector Machines is one tool for this and the outcome is satisfactory. The persons who are suffering from mental health issues will be benefitted from this system.