Description:

Real-time social media (e.g. Twitter) allow users to form ad-hoc communities centered on events, topics of discussion, places and ideas. Yet, finding these communities in the Twitter stream is a challenge — their boundaries are fuzzy, change happens on a minute-by-minute basis and spammer- or bot-driven hijackings of communities are common. In this webcast talk Maksim Tsvetovat author of Social Network Analysis for Startups will introduce a number of ways to address these issues and present an open-source Python-based toolkit for detecting and visualizing communities in Twitter networks.

About Maksim Tsvetovat

Maksim Tsvetovat is an interdisciplinary scientist, a software engineer, and a jazz musician. He has received his doctorate from Carnegie Mellon University in the field of Computation, Organizations and Society, concentrating on computational modeling of evolution of social networks, diffusion of information and attitudes, and emergence of collective intelligence. Currently, he teaches social network analysis at George Mason University. He is also a co-founder of DeepMile Networks, a startup company concentrating on mapping influence in social media. Maksim also teaches executive seminars in social network analysis, including "Social Networks for Startups" and "Understanding Social Media for Decisionmakers".