Social Media Analytics
A web application to estimate and visualize sentiment—an attitude or thought based on emotion—for tweets from Twitter. Each tweet is shown as a circle in an emotional scatterplot, with pleasure on the horizontal axis and arousal on the vertical axis. Other methods of viewing the tweets include topic clusters, a heatmap of tweet counts by sentiment, tag clouds of frequent terms, a timeline of when tweets were posted, and a map of where tweets were posted

We have recently updated our web application for visualizing tweet sentiment. Recent tweets are requested based on user-chosen keywords. An estimate of each tweet's sentiment is made from its text. The results are visualized in numerous ways: in an emotional scatterplot with horizontal pleasure and vertical arousal axes, clustered by topic, in a heatmap that counts tweets by sentiment bins, as a tag cloud of frequent terms, as a timeline of when tweets were posted, as a map of where tweets were posted, and as a list of tweets and their associated sentiment measurements.

Election Visualizations
Election results for North Carolina, each of the 13 congressional districts are subdivided into four quadrants to show which party's candidate the district's voters selected for the 2016 Presidential election (upper-left quadrant), 2012–2016 U.S. Senate election (upper-right), 2016 U.S. House election (lower-right), and 2013–2016 Governor election (lower-left); color represents party (blue for Democrat, red for Republican, green for Independent), and saturation represents the winning percentage (more saturated for higher percentages); the small disc floating over the state shows aggregated state-wide results; incumbent losses are highlighted with textured X's; the height of the state represents the number of electoral college votes it controls

We have recently updated our U.S. election visualizations to include results for the 2016 U.S. elections. We select groups of voters within each congressional district, then compare their voting history by visualizing the winning party for President, U.S. Senate, U.S. House, and Governor elections. Our results show that most voters are not "red" or "blue", that is, they do not vote based on party affiliation alone. More comprehensive strategies that also consider the individual candidates, the state of the nation, and other factors to are used to when an individual decides how to vote.

Perceptual visualization of flow in a simulated supernova collapse
Experimental studies of low-level human visual perception. Our goal is a set of fundamental perceptual guidelines for visualization design.
Multivariate visualization of memory chip validation data
A study of multivariate data, where each data element encodes values for multiple data attributes. Our goal is a set of guidelines for designing effective multivariate visualizations.
Nonphotorealistic visualization of weather conditions over South America
Exploring ways to engage the human visual system through the use of aesthetic visual cues. Our goal is a method to improve memory for detail at important locations in a visualization.
Visualizing the sentiment of tweets containing the keyword "Boston"
An investigation of sentiment—the implied emotion—in short text snippets like tweets, RSS feeds, or Facebook wall posts. Our goal is a set of methods to estimate and visualize sentiment in text.
  • Tweet Viz, a web app to query and visualize tweets from Twitter
Visualizing climatology data over the western United States
Integration of perceptual guidelines into a planning system that uses probabilistic utility to suggest visualizations for a target dataset and analysis tasks. Our goal is a tool that collaborates with an analyst to generate a set of perceptually optimal visualizations that fit the analyst's needs.
Visualizing an ensemble from the Relativistic Heavy Ion Collider
A study of ensembles: large collections of related datasets, for example, from physics or climatology simulations. Our goal is a scalable approach to to manage and visualize ensemble data.
Visualizing association rules for climatology data
Integration of applied mathematical techniques like rule mining, clustering, aggregation, summarization, and outlier detection to structure a dataset prior to visualization. Our goal is to intelligently summarize large datasets by highlighting features of interest at multiple levels of detail.
2012 Texas election results by Congressional district
Visualizations of Presidential, Senate, House, and state Governor election results in each state and Congressional District in the U.S. Our goal is a design that shows how common groups of individuals voted for different elected offices.
Visualizing plankton densities in the northern Pacific Ocean
An investigation of estimating open-ocean plankton densities based on sea surface conditions. Our goal is to use the improved methods to better predict sockeye salmon migration patterns.
Nonphotorealistic visualization of flow in a simulated supernova
An application of perceptual visualization techniques for exploring slices through a simulated supernova collapse. Our goal is a multivariate method that highlights flow properties like vortices, paths, and shock fronts.
Visualizing the 2013 Baltimore–San Francisco Super Bowl game
An investigation of parsing and visualizing play-by-play text for NFL games. Our goal is a design that is simple, effective, and readily accessible to the general public.






Mixed Initiative


Data Analytics


Marine Biology



I am investigating visualization techniques that support rapid, accurate, and effective exploration and analysis of large, complex, multivariate datasets. Many of our approaches harness visual perception. This allows much of the analysis to be performed automatically by the low-level visual system. Research in an area of cognitive psychology known as preattentive processing forms the foundation for our perceptual guidelines. A detailed overview of preattentive processing is available for those who are interested.


A full list of publications is available, with links to citation information, abstracts, and PDF for most of the papers. A PDF version of my CV is also available. Some of our recent publications include the following.


If you want to schedule a meeting with me, please check my calendar for availability, then email me so I can confirm the time is still open.


PhD.   Andrea Villanes Arellano, Adam Marrs, Zeyuan Chen, Shaoliang Nie, Kalpesh Padia, Brian Clee.
MS.   Pallavi Deo.

A complete list of past students is also available.


CSC 600, Graduate Orientation
F 12:50-1:40  1025/1230 EB-II

IAA 501, Introduction to Visualization
Summer 2016, Institute for Advanced Analytics

IAA 502, Text Analytics
Fall 2016, Institute for Advanced Analytics

IAA 502, Visualization Tools
Fall 2016, Institute for Advanced Analytics

IAA 502, Python
Fall 2016, Institute for Advanced Analytics

IAA 502, GIS
Fall 2016, Institute for Advanced Analytics