Xia C., Schwartz, R., Xie K., Krebs A., Langdon A., Ting J. and Naaman M.
With the increasing volume of location-annotated content from various social media platforms like Twitter, Instagram and Foursquare, we now have real-time access to people’s daily documentation of local activities, interests and attention. In this demo paper, we presentCityBeat1, a real-time visualization of hyper-local social media content for cities.The main objective of CityBeat is to provide users – with a specific focus on journalists – with information about the city’s on-goings, and alert them to unusual activities. The system collects a stream of geo-tagged photos as input, uses time series analysis and classification techniques to detect hyper-local events, and compute trends and statistics. The demo includes a visualization of this information that is de-signed to be installed on a large-screen in a newsroom, as an ambient display.
The research was published in In Proceedings, WWW 2014 on 4/1/2014. The research is supported by the Brown Institute Magic Grant for the project CityBeat.