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Livehoods offer a new way to conceptualize the dynamics, structure, and character of a city by analyzing the social media its residents generate. By looking at people’s checkin patterns at places across the city, the researchers create a mapping of the different dynamic areas that comprise it. Each Livehood tells a different story of the people and places that shape it.
Livehoods is a research project from the School of Computer Science at Carnegie Mellon University. Researchers are using machine-learning to study cities.
Our research hypothesis is that the character of an urban area is defined not just by the the types of places found there, but also by the people that make it part of their daily life. To explore this idea, we use data from approximately 18 million check-ins collected from the location-based social network foursquare, and apply clustering algorithms to discover the different areas of the city.
Livehoods allow us to investigate and explore how people actually use the city, simultaneosly shedding light onto the factors that come together to shape the urban landscape and the social texture of city life, including municipal borders, demographics, economic development, resources, geography, and planning.