Information Asymmetry

Project participants:

• Jonathan Vareika
• Pranjal Srivastava
• Jake Brophy

Project supervisors:

• Jörn Boehnke
• Ashwin Aravindakshan

Project goal:

The goal of this project is to perform a network analysis of information diffusion across two social media platforms. The analysis will touch on the impact of an individual’s online community in determining the speed, reach, and type of information spread that occurs and how these differ across platforms. A combination of modern neural network language models and a causal analysis framework will be employed in order to classify and measure the extent to which an online community impacts the content put on the web by an individual. The current working hypothesis is that some properties of the tweets themselves predict greater propagation of information, but that properties of online communities, particularly their historical content, are equal or stronger predictors.