Abstract: Depression is a mental illness that affects an individual negatively. It is considered as a serious disease by mental health care professionals. Depression detection is important to avoid unwanted consequences of not acknowledging the disease. A research was carried out in 2012 and an estimate was found out. It was observed that there were roughly 258000 suicides. Further, it was observed that the age group that was mostly affected was between 15-49 years of age [1]. This estimate informs us that the aforesaid age group is prone to depression. This age bracket spends maximum time on social media and shares their view on it. It reflects their mental condition. This fact encourages us to develop a system to detect the depression level of the users and provide necessary information to the guardians to enable the guardian to take appropriate actions. The system is beneficial in informing the user and their guardian to prevent self-harming or worsening of the condition. The death rate will significantly reduce if the user and the guardian are aware of the mental state of a user. The system is expected to be beneficial to reduce the percentage of death due to depression. It'll provide awareness to users and their guardians by automatically detecting depression [3]. This approach will utilize the emotions of the user detected from videos watched by the user. The title of the video indicates the content or category of the video. This enables us to get an insight to the user’s inclination towards negative polarity.
Keywords: Depression detection, NLP.
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DOI:
10.17148/IJARCCE.2021.10611
