COVID tweet analysis using NLP
Keywords:
COVID19, social media, tweets, Natural Language processing, recurrent neural networkAbstract
The pandemic has taken the world by storm. Almost the entire world went into lockdown to save the people from the deadly COVID-19. With the progression of time, news and mindfulness about COVID-19 spread like the actual pandemic, with a blast of messages, updates, recordings, and posts. Widespread panic manifest as one more worry not withstanding the well-being risk that COVID-19 introduced. Typically, for the most part because of misinterpretations, an absence of data, or now and again by and large deception about COVID- 19 and its effects. General people however have been expressing their feelings about the safety and effectiveness of the vaccines on social media like Twitter. In this study, such tweets are being extracted from Twitter using a Twitter API authentication token. The raw tweets are stored and processed using NLP. The processed data is then classified using a CNN classification algorithm. The algorithm classifies the data into three classes, positive, negative, and neutral. These classes refer to the sentiment of the general people whose Tweets are extracted for analysis.
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