Description:

"Going viral" is a holy grail of internet marketing — but beside the well-known memes and viral campaigns, there is a slower and quieter process of information diffusion. In fact, information diffusion is at the root of "viral nature" of some information. In this webcast, we will talk about the viral nature of information, adoption of attitudes and memes, and the way social networks evolve at the same time as people's attitudes and desires. We will demonstrate some of these principles using models built in Python.

Familiarity with Python programming recommended.

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".