S V Praveen1, Rajesh Ittamalla2, Gerard Deepak2. 1. National Institute of Technology, Trichy, India. Electronic address: praveennitt04@gmail.com. 2. National Institute of Technology, Trichy, India.
Abstract
BACKGROUND AND AIMS: Ever since COVID-19 was declared a pandemic by WHO in late March 2020, more and more people began to share their opinions online about the anxiety, stress, and trauma they suffered because of the pandemic. However, very few studies were conducted to analyze the general public's perception of what causes stress, anxiety, and trauma during COVID-19. This study focuses particularly on understanding Indian citizens. METHODS: By using Machine learning techniques, particularly Natural language processing, this study focuses on understanding the attitude of Indian citizens while discussing the anxiety, stress, and trauma created because of COVID-19 and the major reasons that cause it. We used Tweets as data for this study. We have used 840,000 tweets for this study. RESULTS: Our sentiment analysis study revealed the interesting fact that, even while discussing about the stress, anxiety, and trauma caused by COVID-19, most of the tweets were in neutral sentiments. Death and Lockdown caused by the COVID-19 were the two most important aspects that cause stress, anxiety, and Trauma among Indian citizens. CONCLUSION: It is important for policymakers and health professionals to understand common citizen's perspectives of what causes them stress, anxiety, and trauma to formulate policies and treat the patients. Our study shows that Indian citizens use social media to share their opinions about COVID-19 and as a coping mechanism in unprecedented time.
BACKGROUND AND AIMS: Ever since COVID-19 was declared a pandemic by WHO in late March 2020, more and more people began to share their opinions online about the anxiety, stress, and trauma they suffered because of the pandemic. However, very few studies were conducted to analyze the general public's perception of what causes stress, anxiety, and trauma during COVID-19. This study focuses particularly on understanding Indian citizens. METHODS: By using Machine learning techniques, particularly Natural language processing, this study focuses on understanding the attitude of Indian citizens while discussing the anxiety, stress, and trauma created because of COVID-19 and the major reasons that cause it. We used Tweets as data for this study. We have used 840,000 tweets for this study. RESULTS: Our sentiment analysis study revealed the interesting fact that, even while discussing about the stress, anxiety, and trauma caused by COVID-19, most of the tweets were in neutral sentiments. Death and Lockdown caused by the COVID-19 were the two most important aspects that cause stress, anxiety, and Trauma among Indian citizens. CONCLUSION: It is important for policymakers and health professionals to understand common citizen's perspectives of what causes them stress, anxiety, and trauma to formulate policies and treat the patients. Our study shows that Indian citizens use social media to share their opinions about COVID-19 and as a coping mechanism in unprecedented time.
Authors: Magdalena Sycińska-Dziarnowska; Liliana Szyszka-Sommerfeld; Karolina Kłoda; Michele Simeone; Krzysztof Woźniak; Gianrico Spagnuolo Journal: Int J Environ Res Public Health Date: 2021-11-24 Impact factor: 3.390