1,3: Universidad Politécnica De Valencia, Valencia, Spain; 2: School of Information Engineering, Yangzhou University, Yangzhou 225009, China; 4: Kuvempu University, Shimoga. Karnataka, India
The paper's objective is to carry out a real-time visualization of pandemic sentiment at the very first instance. The paper shows multilevel visualization of sentiment analysis conducted on the covid19 dataset acquired from Twitter. The visualization tools used for real-time data are Google data studio, Python matplotlib, Carto, and Tableau. On Mar 11, 2020, Covid19 was declared a global pandemic, and stage wise lockdown protocols were implemented. The covid19 virus has spread worldwide and consumed millions of people. The impact of the virus is affected not only on the physical body but also on mental health and results in increased distress, depression, anxiety, fear, and panic simultaneously. The data was downloaded using twitter's official API on Mar 11, 2020. Vader sentiment analysis is performed on 3,27,717 tweets downloaded from 200 Megacities globally. The study achieved 50.95% negative and 58.72% positive sentiment and neutral values ranging between 0 to 1 polarity.
Ms. Lavanya, A,Mr. Waqas Ali,Dr. Jaime Lloret,Mr. Vidya Sagar, S. D,Mr. Chivukula Bharadwaj."A Real-time Visualization of Global Sentiment Analysis on Declaration of Pandemic". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.9, Issue 06,pp.104-113, June - 2022, URL :https://ijcert.org/ems/ijcert_papers/V9I602.pdf,
: Covid19; Geo-Spatial; Temporal Data; Pandemic; Sentiment; Visualization;
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