Paragon Science has developed a technology that examines dynamic networks and identifies the entities that show the highest levels of abnormal change. This application finds the most viral URLs in a twitter network.
Paragon Science has developed a technology that examines dynamic networks and identifies the entities that show the highest levels of abnormal change.
Here is an application to March 2012 Twitter data related to President Barack Obama,
where they identified a set of highly viral web links as key indicators of trends and user interest.
In this video, small blue spheres represent Twitter users whose tweets reference websites, which are displayed as cubes. Each line represents a link between a user and a referenced URL. At the end of each day, the viral URL that exhibits the greatest change in user interest for that date is labeled and colored according to the relative change (blue=least, red=most). After the days of March 2012 are shown, the users' nodes are colored according to their respective communities, and network is rotated to show the community structures. The end of the video highlights the top three viral websites in this dynamic social network.