Michael Fire, previous eScience postdoctoral fellow, and Carlos Guestrin, senior data science fellow, have published a paper titled “The rise and fall of network stars: analyzing 2.5 million graphs to reveal how high-degree vertices emerge over time” in the Journal of Information Processing and Management.
Fire and Guestrin constructed the largest publicly available network evolution dataset to date, which contains 38,000 real-world networks and 2.5 million graphs. Moreover, their research helps us to better understand how new trends emerge in the real world (for example, how one might become a YouTube star.)
The study took about two years to complete, with a revision process taking an additional year and a half. The pair also created a video on YouTube (see below) which helps to explain their research.
Learn more about this project in the eScience Research Feature “Fake profiles detection on online social networks.”