Methods to Perform Opinion Mining and Sentiment Analysis to Detect Factors Affecting Mental Health
Ravindra Kumar
Ravindra Kumar*, Technical Account Manager, Navvis Healthcare, St. Louis MO.

Manuscript received on September 08, 2021. | Revised Manuscript received on September 15, 2021. | Manuscript published on October 30, 2021. | PP: 70-72 | Volume-11 Issue-1, October 2021. | Retrieval Number: 100.1/ijeat.F30250810621 | DOI: 10.35940/ijeat.F3025.1011121
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Sentimental analysis and opinion extraction are emerging fields at AI. These approaches help organizations to use the opinions, sentiments, and subjectivity of their consumers in decision-making. Sentiments, views, and opinions show the feeling of the consumers towards a given product or service. In recent years, Opinion Mining and Sentiment Analysis has become an important tool to detect the factors affecting mental health. It’s Also true that human biasness is available in giving opinions, but it can be eliminated through the use of algorithms to get better results. However, it is crucial to remember that the developers are human and might pass the biasness to the algorithms during training. The main target of this paper is to give background knowledge on opinion extraction and sentimental analysis and how factors affecting mental health can be collected. The paper aimed to use interested individuals in knowing some of the algorithms in opinions extraction and sentimental analysis. The paper also provides benefits of using sentiment analysis and some of the challenges of using the algorithms.
Keywords: Opinion Mining and Sentiment Analysis has become an important tool to detect the factors affecting mental health.