In his article Dr. Duncan Shaw (U. Nottingham) raises the specter that the recent flood of media stories about leaks, hacks and misuse of personal data is eroding people’s trust in the concept of ‘big data’ to the extent that they may soon rise up in a revolt against the very notion of ‘big data’.
Computational Social Science (CSS) lies at the intersection of applied mathematics, statistics, computer science, and the social sciences, combining ideas from each of these to discover and understand patterns of individual and group behaviours.
The rapid growth of internet services like Wikipedia, Google, Facebook, YouTube, Twitter, and the growing ubiquity of Smartphones, Wi-Fi and other ‘smart’ technologies that (can) collect data about human behaviour are fundamentally changing the way in which we can learn about the social world. In the age of “big data” information about human behaviour is being collected on a scale and never before possible and with tremendous granularity and precision. The ability to collect and process such data will enable researchers to address core questions in the social sciences in new ways and opens up new areas of inquiry.
As Internet and computer usage expands, so does the availability of large-scale, digitized information on social phenomena. The capacity to manage and analyze this information is increasingly important to multiple social domains and institutions in society. Computational sciences afford a variety of techniques to collect, manage and analyze this vast array of information, while the social sciences afford a variety of theories and understandings that can guide computational analysis. On their own, computer science can create new and useful technologies and social scientists can address important social problems and issues, but together they can apply computational techniques to analyze and explain incredibly vast and detailed information on social phenomena – in a theoretically informed way – which we could not imagine possible in the prior decade.
Against this considerable promise stands the equally pressing concern of protecting individual privacy. Privacy is already an important issue for all industries that collect digital information about their consumers. As CSS starts to combine the multitude of data with new insights, analytical and modelling methods, it raises increasingly serious questions about individual privacy, even more than are posed by existing commercial platforms. Precisely these questions, in fact, have already been raised by recent revelations of the NSAs Prism project, which also appears to be an attempt to combine data from multiple sources. The responsible development of CSS therefore requires that ethical issues must be considered at all stages.
09:30 – 10:00 Tea/coffee
10:00 – 10:15 Dr. Ansgar Koene (University of Nottingham/University of Birmingham) – Welcome/Introduction
10:15 – 11:15 Prof. Steven Bishop (UCL) – ‘Models for social systems: What are they good for?’
11:15 – 11:45 Prof. Chris Baber (University of Birmingham) – ‘Building dark Networks: analysis modelling of network structures in covert groups’
11:45 – 12:00 Coffee
12:00 – 12:30 Dr. Ansgar Koene (UoN/UoB) – ‘Citizen centric approaches to Social Media analysis (CaSMa)’
12:30 – 13:00 Dr. Mirco Musolesi (University of Birmingham) – ‘Understanding Cities using Social Media Data’
13:00 – 13:30 Dr. Emmanouil Tranos (University of Birmingham) – ‘Mobile Phone Usage in Complex Urban Systems: a space-time, aggregated human activity study’
13:30 – 14:30 Lunch
14:30 – 15:30 Dr. Suzy Moat (Warwick) – ‘Predicting human behaviour with Internet data’
15:30 – 16:00 Dr. Colin Rowat (University of Birmingham) – ‘Applying mechanised reasoning to economics’
16:00 – 16:15 Coffee
16:15 – 17:15 Discussion/Grant application preparation