Daniele Quercia - Yahoo! Research Barcelona Digital Security
Date: - Location: Eurecom
Abstract: For the last few years, we have been studying existing social media sites and created new ones in the context of London. By combining what Twitter users in a variety of London neighborhoods talk about with census data, we showed that neighborhood deprivation was associated (positively and negatively) with use of emotion words (sentiment) and with specic topics. Users in more deprived neighbourhoods tweeted about wedding parties, matters expressed in Spanish/Portuguese, and celebrity gossips. By contrast, those in less deprived neighborhoods tweeted about vacations, professional use of social media, environmental issues, sports, and health issues. Also, upon data about 76 million London underground and overground rail journeys, we found that people from deprived areas visited both other deprived areas and prosperous areas, while residents of better-off communities tended to only visit other privileged neighborhoods - suggesting a geographic segregation etc. More recently, we created and launched two crowdsourcing websites. First, we launched urbanopticon.org, which extracts Londoners' mental images of the city. By testing which places are remarkable and unmistakable and which places represent faceless sprawl, we were able to draw the recognizability map of London. We found that areas with low recognizability did not fare any worse on the economic indicators of income, education, and employment, but they did significantly suffer from social problems of housing deprivation, poor living conditions, and crime. Second, we launched urbangems.org. This crowdsources visual perceptions of quiet, beauty and happiness across the city using Google Street View pictures. Speaker's Bio: Daniele Quercia recently joined Yahoo! Labs in Barcelona. Before that, he was a Horizon Senior Researcher at The Computer Laboratory of the University of Cambridge. He is interested in the relationship between online and offline worlds and his work has been focusing in the areas of data mining, computational social science, and social computing. Previously, he was Postdoctoral Associate at the Massachusetts Institute of Technology where he worked on social networks in a city context. For his PhD at the University College London, he created algorithms with which co-located mobile users share pictures and videos using short-range technologies, and his thesis was nominated for BCS Best British PhD dissertation in Computer Science. During his PhD, he was a Microsoft Research PhD Scholar and MBA Technology Fellow of London Business School, and he also interned at the National Research Council in Barcelona and at National Institute of Informatics in Tokyo. He studied at Politecnico di Torino (Italy), Karlsruhe Institute of Technology (Germany), and University of Illinois (USA).
Urban*: Crowdsourcing for the Good of London
