Brainstorm here — please list your name and ideas you might have.
Isaac Mackey (Computer Science) – I’m interested in the use of Twitter bots to influence real-time public opinion (instead of simply promoting products or accounts). Specifically, I want to evaluate techniques for using Twitter bots to dominate the narratives and opinions of developing news events. As for the production element of this project, I would like to automate the process of Twitter bot creation. If you’re interested, email me using the address in the class emails.
Yun Suk Chang (Computer Science) – I am interested in visualizing information in Virtual or Augmented Reality. For the course project, I am thinking about visualizing twitter’s geo-tag information across the virtual Earth.
Ali Rahman (Comparative Literature) – I’m interested in looking at algorithmic bias and perhaps especially the obsession (and pitfalls) with finding the most efficient solution to problems. I’m also concerned with how normative or mainstream opinions and interpretations are formed and take hold of populations no matter how flawed. For the final project, search and trending are probably the most relevant topics for me, but I may also want to think about network visualizations.
Virginia Leavell (Sociology). I’m interested in twitter bots and how they influence politics and consumption. There’s a group that wrote an algorithm to identify twitter bots that might be fun to play with. I’m also interested in algorithms and financial trading, and the fact that around 50% of trades on wall street are automated by algorithms, and that firms are naming algorithms to their boards of directors.
Brandon Huynh (Computer Science). I’m interested in looking at trust in information, especially news articles or scientific data. I’d like to explore how visualizations and interaction techniques can be used to build (or reduce) trust when presented with new information. For the final project, I’d be interested in visualizing or creating a fact checker for news. Or perhaps examining (profiling) user’s backgrounds to understand their existing preconceptions.