Kris Shaffer, Ph.D. (Yale University, 2011), is an Instructional Technology Specialist and Adjunct Instructor of Computer Science and Digital Studies at the University of Mary Washington. He is also a Contributing Editor for Hybrid Pedagogy and the lead author and editor of Open Music Theory.

Kris is a data scientist with a background in computational musicology, a digital media specialist, a software developer, and a published author. Recently, he has been developing open-source software and analytics tools for education, particularly in the context of critical digital pedagogy, open educational resources (OER), and UMW's Domain of One's Own initiative. He is also studying and writing on the spread of misinformation and disinformation through digital platforms ― both independently and for the volunteer collective, Data for Democracy.

Explore Kris's projects, articles, and essays below. Or visit the complete blog archive or his GitHub profile.

featured projects

D4D

A volunteer collective using data science for social good.

DoOO Analytics

Public dashboard and private analytics reports for Domain of One's Own.

DoOO Corpus

Mining and analyzing text from 300+ articles about Domain of One's Own worldwide.

BB-Cluster

Using Markov models and K-means cluster analysis to analyze harmonic practices in the McGill Billboard dataset.

Peasy

Super-simple content management system designed for open-licensed content.

Web Annotations

Hypothes.is aggregator embeds hypothes.is annotations on WordPress pages and posts.

featured article

Spot a Bot: Identifying Automation and Disinformation on Social Media

There are bots everywhere, or so it seems. Some of these bots can be fun. But all too often, automated and otherwise high-volume social media accounts exist to deceive. Not only do they try to make readers believe they are real people, but they also participate in the spread of disinformation and malware, as well as coordinated harassment campaigns.

The bad news is that they often succeed in their deceptive ventures. But the good news is that most bots ― and their close cousins, “sockpuppets” and “trolls” ― exhibit some clear tell-tale signs. What follows is a list of those signs, based on our research into bots, sockpuppets, and disinformation on Twitter. With these signs, anyone can spot a bot, and resist the spread of disinformation online.

Read more at Data for Democracy... (Co-authored with Bill Fitzgerald.)