An Exploratory Case Study on COVID 19 Omicron using Twitter Analytics
Keywords:
sentiment analysis, corona, social media, NLTK vadarAbstract
The Covid-19 pandemic is the most disruptive event worldwide and it majorly affects public health. Social media plays a significant role in people's lives, and constantly gets bombarded with messages, tweets, memes, and posts about Covid-19 and Omicron. The Omicron is another variant of Covid-19 which is widely spread across the globe thereby increasing the percentage of people being affected. During this research, the tweets are collected using the Twitter API to perform Sentiment Analysis. An exploratory case study has been developed using Twitter analytics, relying upon pragmatic evidence stemming from the case study about Covid-19 and Omicron. This research aims at scrutinizing people's thoughts and opinions regarding omicron and covid by comparing the results. The tweepy library for accessing the Twitter API and the Valence Aware Dictionary for Sentiment Reasoning (Vader), a lexicon and rule-based sentiment analysis tool accessible in the Python programming language, are used.
Throughout this research 80,000 tweets were fetched with hashtags #covid, #covid19, #coronavirus, #corona, and other sets of 80,000 tweets were fetched with hashtags #Omicron, #Omicold, #OmicronVariant, #OmicronVirus around the globe. The tweets were obtained from 22/12/2021 to 30/04/2022.
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