id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-123103-pnjt9aa4	Ordun, Catherine	Exploratory Analysis of Covid-19 Tweets using Topic Modeling, UMAP, and DiGraphs	2020-05-06		.txt	text/plain	6981	495	65	Our contributions are applying machine learning methods not previously analyzed on Covid19 Twitter data, mainly Uniform Manifold Approximation and Projection (UMAP) to visualize LDA generated topics and directed graph visualizations of Covid19 retweet cascades. We then visualized "retweet cascades", which describes how a social media network propagates information [23] , through the use of graph models to understand how dense networks become over time and which users dominate the Covid19 conversations. The paper begins with Data Collection, followed by the five stages of our analysis: Keyword Trend Analysis, Topic Modeling, UMAP, Time-to-Retweet Analysis, and Network Analysis. Chinese social media may not represent similar behaviors with American Twitter and this analysis does not take into account multiple factors that imply retweeting behavior to include the context, the user's position, and the time the tweet was posted [44] .	./cache/cord-123103-pnjt9aa4.txt	./txt/cord-123103-pnjt9aa4.txt