1Cademy - Mining Trends of COVID-19 Vaccine Beliefs on Twitter with Lexical Embeddings Methodology

Concept

Mining Trends of COVID-19 Vaccine Beliefs on Twitter with Lexical Embeddings Methodology

Used Snscrape library to collect more than 1 million tweets from June 2020 to February 2021 related to vaccines through keywords and hashtags
Created 10 lexical categories for psychometric evaluation of tweets on COVID-19 vaccine – 6 emotions (hesitation, anxiety, sorrow, faith, contentment, urgency) and 4 influencing factors (misinformation, vaccine rollout, inequities, health effects) and made a list of seed words for each category
Using cosine similarity, researcher measured how close the tweet contents were to seed words in each of the categories
To determine correlation, pairwise Pearson correlation, weighted networks of categories and edge-strengths, and community detection were created and implemented