Web Science and Digital Libraries Research Group

Figure 1: Screenshot of 24 of 27 Democratic candidates  hopeful of the Presidential nomination on May 25, 2019 (Source: The Washington Post) In our previous post,  Twitter Follower Growth for the 2020 Democratic Candidates , we used the Twitter follower growth between 2019-01-01 and 2019-08-23 as a proxy to measure popularity of the Democratic candidates and categorized the campaign of each candidate based on their absolute Twitter follower growth into four categories: already popular, big winners, nobody noticed, and beneficial .  Since our previous post, all the candidates except Joe Biden, the presumptive presidential nominee, have dropped out. In this post, we revisit the Twitter follower growth of all 27 Democratic candidates by extending our study to between 2019-01-01 and 2020-04-18. We plotted an  interactive D3 Twitter follower graph to show the trends in the absolute increase of the followers for each candidate .    Twitter and Web Arc...

(Previous semester highlights posts: Spring 2017 , Spring 2016 , Spring 2015 , Spring/Fall 2013 , Fall 2012 , Fall 2011 ) Here are a few projects that I'd like to highlight from Fall 2017. (All class projects are listed in my InfoVis Gallery .)  All of the projects were implemented using the D3.js library. World Leader Interactions on Social Media (Twitter)  Created by Grant Atkins This project (available at http://www.cs.odu.edu/~gatkins/world-leader-vis/app/ ) provides an interactive dashboard to visualize ways Twitter list data can be used and represented. This visualization uses the World Leaders list on Twitter , with the addition of a few world leaders not on the list, to derive information and visualize shared information among these users. The goal of this visualization is to show shared term usage among world leaders, see which times tweets are more likely to be sent out, the sentiment of the users, and the decay of data allocated in a static decreasin...

"Team Turtle" in Archive Unleashed in Washington DC (from left to right: N. Chah, S. Marti, M. Aturban , and I. Amin) The first presidential debate (H. Clinton v. D. Trump) took place on last Monday, September 26, 2016 at Hofstra University , New York. The questions were about topics like economy, taxes, jobs, and race. During the debate, the candidates mentioned those topics (and other issues) and, in many cases, they associated a topic with a particular place or a US state (e.g., shootings in Chicago, Illinois, and crime rate in New York). This reminded me about the work that we had done in the second Archives Unleashed Hackathon , held at the Library of Congress in Washington DC. I worked with the "Team Turtle" ( Niel Chah , Steve Marti , Mohamed Aturban , and Imaduddin Amin ) on analyzing an archived collection, provided by the Library of Congress, about the 2004 Presidential Election (G. Bush v. J. Kerry). The collection contained hundreds of archived w...

(Note: This wraps up the current series of posts about visualizations created either by students in our research group or in our classes. I'll post more after the Spring 2015 offering of the course.) I've been teaching the graduate Information Visualization course since Fall 2011.  In this series of posts, I'm highlighting a few of the projects from each course offering.  (Previous posts: Fall 2011 , Fall 2012 , 2013 ) The final visualization in this series is an interactive visualization of the World Health Organization's global influenza data, created by Ayush Khandelwal and Reid Rankin in the Fall 2013 InfoVis course. The visualization is currently available at https://ws-dl.cs.odu.edu/vis/flunet-vis/ and is best viewed in Chrome. The  Global Influenza Surveillance and Response System (GISRS) has been in operation since 1995 and aggregates data weekly from laboratories and flu centers around the world. The FluNet website was constructed to provide access t...

(Note: This is the first in a series of posts about visualizations created either by students in our research group or in our classes.) The US Navy runs a Hearing Conservation Program (HCP) which aims to protect the hearing and prevent hearing loss in service members.  Persons who are exposed to levels in the range 85-100 dB are in the program and have their hearing regularly tested.  In the audiogram, there is a beep sounded at different frequencies with increasing volume.  The person being tested raises their hand when they hear the beep and the frequency and volume (in dBA) are recorded.  A higher volume value means worse hearing (i.e., the beep had to be louder before it was audible). Not only are people in the HCP regularly tested, but they are also provided hearing protection to help prevent hearing loss.  The audiogram data includes information about the job the person currently holds as well as if they are using hearing protection. Researchers are in...