Twitter Data Visualization – #climatechange

About the Visualization Methods

These are a repertoire of data visualization methods applied to a dataset of tweets containing the hashtag ‘climatechange’ collected during a period from November 20 to December 5, 2018. Methods include a network graph visualization of the entire dataset, frequency count plots of the top 20 tweets (i.e. the tweets with the most retweets), temporal scatter plots showing the lifespan of a tweet with scatter dot size representing follower counts which help shed light on how a user with a high number of followers can ‘resurrect’ the life of a tweet, and 3D data visualization of the same methods combined into a single interactive viz using the ANTz 3D data viz program.

View more visualizations here.  

About the #climatechange dataset

This dataset was collected from November 20 to December 5, 2018, with the Twitter API using the streaming search option to gather tweets and retweets which used the hashtag #climatechange. There are 457,294 tweets and retweets. There are 138,305 original tweets and 318,989 retweets.

Fractal Pattern Drawing Program

I developed a drawing program in JavaScript and the HTML5 canvas element which was initially intended to draw fractal trees and to create artsy fractal forests. It has since expanded to include other geometric patterns and I have added some presets to highlight some of the more interesting capabilities.  please drop me a line on Twitter with feedback if you are so inclined.

https://iluvdata.org/fractal_drawing/index.php

 

 

Twitter Disinformation Visualization

These are some examples of visualization work I did* in an effort to gain insight into disinformation campaigns and twitter bot behavior.

https://www.iluvdata.org/twitter/disinfo/summary.html

Twitter Bot Viz

Twitter disinfo viz

*This work was funded by the Office of Naval Research (Grant N-00014-18-1-2012). Thanks to co-PIs Jen Zeimke and Kate Starbird, with additional acknowledgement to Dave Warner, Robert Alexander, Peter Raymond, Mike Winters, and the rest of the team who made such important contributions. Hat tip to Shane Saxon, developer of the ANTz visualization tool.

 

COVID-19 Geospatiotemporal Visualization of Confirmed Cases, Global Spread.

Explore my most recent work, visualizing COVID-19 coronavirus global spread of confirmed and new cases.

Above image: Detail of COVID-19 deaths globally.

View more COVID-19 visualizations here: https://www.iluvdata.org/covid19/

Data source: Center for Systems Science, Johns Hopkins University, https://github.com/CSSEGISandData/2019-nCoV

Check out more of my 3D hyperglyph visualizations at https://www.edworlds.com/antz/toroids/.