Unmasking of Heart Disease Symptoms Using the COVID-19 Vaccine Dataset in Twitter: Text Feature Extraction, Sentiment Analysis

N. Shyamala Devi Vels Institute of Science, Technology, and Advanced Studies, India K. Sharmila Vels Institute of Science, Technology, and Advanced Studies, India J. Grace Hannah Vels Institute of Science, Technology, and Advanced Studies, India https://orcid.org/0000-0002-9997-3157 Unmasking of Heart Disease Symptoms Using the COVID-19 Vaccine Dataset in Twitter Text Feature Extraction, Sentiment Analysis

The chapter delves into the intricate web of conversations surrounding the COVID-19 vaccine on Twitter and explores its potential association with heart disease symptoms. In an era where social media plays a pivotal role in shaping public perception and disseminating information, understanding the narratives and concerns around vaccine safety is of paramount importance. Leveraging a dataset curated from Twitter discussions, the authors employ natural language processing techniques and sentiment analysis to unearth insights regarding heart disease symptoms mentioned in the context of COVID-19 vaccination. This research unearths the sentiments, trends, and possible correlations within this corpus of Twitter data. By unmasking potential connections between COVID-19 vaccination and heart disease symptoms, this study contributes to a more comprehensive understanding of vaccine-related discussions and their implications for public health.
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