This project will examine temporal, social, and geographic patterns in large-scale social awareness streams (SAS) data for local communities. SASs, such as Twitter and Facebook, are radically altering our society's information fabric. These new communication platforms are used by millions of people to share brief status messages in socially connected public forums. These messages expose vast amounts of data from, and about, local geographic communities -- data that reflect people's activities, interests, and attention, in thousands of localities worldwide. Using this vast and still emerging sources of data, this research program will make SAS into a viable and significant source of information with capacity to transform our understanding of local communities.
As a first activity, the research will adapt algorithms from other fields to identify temporal patterns in SAS data that are stable across multiple communities. Importantly, the work will reason about how and when these patterns break. For example, SAS data may expose sleeping patterns in a community, and help identify mass anxiety when these patterns break. Further, the project will develop methods to identify differences in SAS patterns between local communities, and connect these findings to other sources of data. Next, the research will develop methods to compare how different groups (e.g., by age or ethnicity) use specific neighborhoods and cities. Finally, the work will examine the relations between local communities and network ties as reflected in SAS data. The findings will form the basis for developing novel models of computation for SAS systems, and inform the creation of tools and applications geared to re-imagine SAS as reliable information systems for local communities.
The project is rooted in social computing and in human-centered approaches to development of new technology. As such, the work entails interdisciplinary investigation using methods and research questions drawing on fields as diverse as information and computer science, sociology, and communication. The project will tackle significant information challenges that these SAS and other social computing platforms present, such as the scale, bias, and the increasing amount of noise and spam, as well as the brevity and lack of context of posted messages. The research will develop novel methods and approaches to using these new information sources to extract knowledge about, and for, local communities.
The research focus on social media and local communities lends itself well to outreach and education activities. The outreach efforts will enhance the connection of public libraries to the communities they serve, and relate the social media experiences of people?s everyday lives to scientific challenges. Participatory design workshops and visits to select educational institutions will engage individuals currently underrepresented in the sciences. An interdisciplinary education program will prepare a diverse set of students at all levels to lead the next generation of innovation, research, and education in socio-technical systems.
Finally, this project will have a significant impact on our society. By leveraging SAS as novel sources of information, the research will lay the foundation for new studies about local communities. The resulting technologies and insights will inform and transform the work of local governments, news organizations, planners, and researchers, as well as local residents and activists, allowing them to take full advantage of these new repositories of human expression and thought with relevance to such diverse social challenges as emergency response, resource planning, and public health.
