Abstract
Depression is the world’s fourth leading disease and will be in the second in 2020 according to the statistics of World Health Organization.Depression affects many people irrespective of their age, geographic location, demographic or social position and more commonly affects females than males.Depression is a mental disorder which can impair many facets of human life. Though not easily detected it has intense and wide-ranging impressions. Although many researchers explored numerous techniques in predicting depression, still there is no improvement and the generations are facing higher rate of depression. It is believed that the depression detection algorithms can be more accurate and their performance can be better if they rely on artificial intelligence. On considering these factors, it is planned to perform a survey on the application of various machine learning techniques that have been used in the domain of sentimental analysis for depression detection.
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CITATION STYLE
Soundariya, R. S., Nivaashini, M., Tharsanee, R. M., & Thangaraj, P. (2019). Application of various machine learning techniques in sentiment analysis for depression detection. International Journal of Innovative Technology and Exploring Engineering, 8(10 Special Issue), 292–297. https://doi.org/10.35940/ijitee.J1052.08810S19
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