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Archive for the ‘Economics’ Category

Photo by Lloyd DeGrane.

Photo by Lloyd DeGrane.

Cities draw their strength from community and diversity, when people from different backgrounds work together in close proximity on big problems. So to unleash the potential of city data, it only makes sense to replicate that mixing bowl effect in the context of research. To formally kick off the new Urban Sciences Research Coordination Network (USRCN), 80 experts representing a broad range of disciplinary knowledge met in downtown Chicago to forge new connections and grand ideas for projects that harness data for the benefit of the modern city.

Computer scientists, mathematicians, public health and education experts, architects, urban planners, social scientists, artists and more gathered inside the ballroom of the School of the Art Institute of Chicago on February 15th with an ambitious goal: form a new interdisciplinary research community for data-driven urban science. Co-hosted by the Urban Center for Computation and Data (UrbanCCD) and the University of Chicago Urban Network and funded by the National Science Foundation, the event was meant as both social mixer and brainstorming session.

“We were asked by the NSF to create this research coordination network as a network of people, not computers,” said Charlie Catlett, director of UrbanCCD. “If you can put teams together that are interdisciplinary and also cut across these experience types, then we can begin to study the city in a way that none of us could do just as individuals or small groups.”

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Depending on your perspective, Twitter is either a colossal waste of time or an addictive tool that has changed the way people interact online. But there’s no arguing that the service generates a ton of data, with roughly half a billion tweets posted around the world each day. As with any enormous data set, there are likely valuable signals to be captured from within that massive noise…with the right tools. In an award-winning master’s thesis, Computation Institute scientist Mattias Lidman set out to see if he could use the avalanche of daily tweets to predict the future winners and losers of reality shows and stock markets.

Financial analysts have long looked for an information advantage in playing the market, a way of knowing and acting upon important news before other investors. Logically, people have tried to use internet activity to make predictions about future market trends, including a paper last year that looked at web search terms and trading volumes. But Twitter offers a new promising data mine from which to extract predictions, due both to its global popularity and its ephemeral nature. While writing a news article or a blog post (usually) requires both time and a computer, Twitter’s portability and brevity enables more frequent, train-of-thought use.

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