Understanding the COVID-19 Pandemic Through Social Media Discourse
Explore the polarization of public health topics on Twitter related to COVID-19 and vaccines. Analyze over 13 million tweets to understand user dominance, sentiment, and discourse patterns. Use NLP and machine learning for topic modeling and sentiment analysis. Goals include gaining insights into Twitter discourse, building machine learning models, and applying real-life concepts to data.
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UNDERSTANDING THE COVID-19 PANDEMIC THROUGH SOCIAL MEDIA DISCUSSION Brenna Rojek, Bryant University brojek@bryant.edu, (401)595-3215 Suhong Li, Bryant University sli@bryant.edu Gaurav Khanna, University of Rhode Island gkhanna@bryant.edu March 9th, 2022
UNDERSTANDING THE COVID-19 PANDEMIC THROUGH SOCIAL MEDIA DISCUSSION GOALS Study polarization of public health topics Americans use social media as a platform to obtain news This project will explore Twitter discourse around the topic of COVID-19, seeking to understand which users or topics dominate discourse. The broader significance of this project is to gain insight on how information* is spread on the Twitter platform. Hugging Face machine learning will be used to predict the emotion of the tweets.
UNDERSTANDING THE COVID-19 PANDEMIC THROUGH SOCIAL MEDIA DISCUSSION Leading Users Tweet Count by State POTUS 31494940 Pink 31647994 JLo 45240429 nytimes 49426475 jimmyfallon 51873193 User BillGates 53850311 selenagomez 65054698 YouTube 73106161 realDonaldTrump 85200430 BarackObama 130103130 0 50000000 100000000 150000000 Follower Count The project will explore a dataset of over 13 million tweets with the keywords related to COVID-19 and vaccine or vax , spanning from March 2020 to October 2021. This project will use machine learning and natural language processing in Python to implement topic modeling and sentiment analysis on the tweets in the dataset.
UNDERSTANDING THE COVID-19 PANDEMIC THROUGH SOCIAL MEDIA DISCUSSION TIMELINE Learn about NLP and conduct preliminary research Extensive Analysis using NLP and Machine Learning Conclude Analysis and Wrap Presentation March June February April July Launch Presentation & Data Exploration Interpret Results
UNDERSTANDING THE COVID-19 PANDEMIC THROUGH SOCIAL MEDIA DISCUSSION WHAT I HOPE TO LEARN Understanding more about the workings of NLP How to build my own machine learning model Applying real life concepts to the data Gain insight about Twitter discourse about COVID-19 and vaccinations Hugging Face
UNDERSTANDING THE COVID-19 PANDEMIC THROUGH SOCIAL MEDIA DISCUSSION GOALS FOR NEXT MONTH Read Hugging Face Textbook (Natural Language Processing with Transformers: Building Language Applications with Hugging Face, By Lewis Tunstall, Leandro von Werra, Thomas Wolf, 2022 February, O Reilly) Explore data on the cluster Get comfortable with utilizing the cluster
UNDERSTANDING THE COVID-19 PANDEMIC THROUGH SOCIAL MEDIA DISCUSSION HELP RECOMMENDATIONS STUDIES
