CUR - The Council on Undergraduate Research

A Covid-19 Word Cloud Map based on Twitter

Umaid Ali Khalid and Dr. Daehan Kwak School of Computer Science and Technology, Kean University, Union, NJ 07083

Covid-19 has taken over the whole world and continues to spread exponentially. People are unaware that what areas are safe to visit and what areas are not contaminated with the virus. Many applications show Covid-19 data but are limited to either countries, states, or counties and do not provide exact detail of how dangerous that area is in the form of words. On the other hand, Twitter, a popular social media app, contains thousands of tweets posted by people that discuss the Coronavirus situation based on different locations. The purpose of this study is to explore the Covid-19 condition at different locations based on tweets. The information related to Coronavirus for a particular location is accessible to derive from the people's tweets who post about their local area.  A tweet mining system will be built to crawl and collect tweets that consists of Covid-19 information using the Twitter Streaming API. A python program is used to build an interface for crawling and collecting the tweets from Twitter using tags, geotags, or any other relevant information that provides appropriate data about the particular area. Later, the keyword metadata would be obtained and transfer to the interface for building a word cloud (or tag cloud) to visualize the tweets data. Finally, a Google Map API would be used to embed the word cloud in a specific location. In conclusion, the topics mainly discussed regarding Covid-19 will be visualized on a map to better understand what the people’s interest is in to gauge a better understanding of what people are mainly concerned of.

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