Paragon Science Featured on O'Reilly Media
Identifying viral bots and cyborgs in social media
Analyzing tweets and posts around Trump, Russia, and the NFL using information entropy, network analysis, and community detection algorithms.
Dr. Kramer joined the board of technical advisors of data.world, which is a Public Benefit Corporation focused on building the most meaningful, abundant, and collaborative data resource in the world.
Dr. Kramer presented his research on more than 120 M tweets related to the 2016 U.S. presidential elections in a talk entitled “Finding Key Influencers and Viral Topics in Twitter Networks Related to ISIS, Brexit, and the 2016 Elections.”
Dr. Kramer presented a talk “Finding Emerging Topics Using Chaos and Community Detection in Social Media Graphs” in a joint meetup of Austin Data Geeks and Austin Graph.
A sample of 2.5M tweets mentioning “Ebola” was collected during November 5–12, 2014. The titles of the 6227 web pages referenced by the tweets were used to cluster the web pages into roughly 100 topics. Paragon Science’s patented dynamic anomaly detection software identified the top five most-anomalous topics. This research demonstrates how these techniques allow […]