Moodshift: An App for Depression
Author(s):
Nidhi Soni, Shruti Nirbhavane, Prabhleen Kaur Saluja, Jaya Mane, Shobha Raskar
Keywords:
Chatbot, depression detection, machine learning algorithm, mental healthcare, natural language generation, natural language processing, voice-based chatbot.
Abstract
Chatbots were introduced to mimic human behavior. This concept can be applied to mental healthcare apps wherein the users anticipate they are talking to a mental health professional. Instead of being a static web app, chatbots are becoming more prevalent in mental healthcare apps. They mimic the human behavior by asking users to provide a mental health diagnosis. There are many vulnerable groups who will suffer from psychological distress, anxiety, depression, substance abuse, suicide and suicidal behavior due to economic recession, insecure job situation, unemployment, lower socio-economic status. The effects on mental health will last several years after the pandemic ends. Delay in seeking professional help because of stigma surrounding mental health will cause more issues,”. Voice-based chatbot makes it casual, intuitive, and direct. Interaction with the chatbot happens through natural language whereas its evaluation happens through natural language processing and natural language generation. A machine learning algorithm is used to classify depression detection results according to the severity.
Article Details
Unique Paper ID: 151788

Publication Volume & Issue: Volume 8, Issue 1

Page(s): 927 - 929
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