Computationally-mediated civic participation is emerging as a solution to contemporary problems associated with economic and social issues such as healthcare, energy sustainability, education, environmental protection, and disaster response. The NSF-funded research project conducted by Ben Shneiderman, Alan Neustadtl, and Catherine Plaisant at the University of Maryland will study reasons for successes and failures of the community safety system, Nation of Neighbors. The results will enable interventions to shift the balance towards increasing success. One product of the research will be a computer-based Community Analysis Visualization Environment (CAVE) that will enable community managers to use a visual analytic toolkit to take the pulse of their communities by identifying effective and ineffective components of the community participation program, and will enable researchers to compare large numbers of communities to understand the features that distinguish successful from failing community participation programs. The project will test the four-stage Reader-to-Leader Framework -- which assumes that participation moves from reader to contributor to collaborator to leader, with fewer and fewer participants moving into each subsequent stage -- by studying community manager strategies for coping with the practical challenge of increased participation as well as threatening disruptions caused by external events, malicious attacks, harmful rumors, and disaffected members.
In addition the results will have general implications for many computationally-mediated civic participation systems such as those designed for coping with natural disasters (earthquakes, toxic waste discharges, etc.), medical outbreaks (food poisoning, flu, pandemics, etc.), and human threats (terrorists, serial killers, bombers, arsonists, etc.). The computational tools developed for the project will also be useful to researchers studying community participation networks. The research may also provide useful insights into the working of other types of social networks and might have implications for organizations where information is shared by large numbers of people, such as hospitals and school districts.
Community safety activists have the potential to be more effective by using emerging social media tools. Lowered communications barriers enables homeowners and renters to know more of the people in their community and cooperate more effectively. Then they can use these media to learn about local activities that might increase their safety, while helping protect their neighbors from threats. However, our findings demonstrate that successful communities require devoted leaders who invite new members, ask meaningful questions, and post responses to community member’s questions. Another important finding is that members who don’t ask or post questions still feel that their community is safer because of the discussion groups let them know what is happening. In this project we designed, developed and tested several software tools to help us analyze our testbed communities (i.e. Nation of Neighbors communities). For example ManyNets, an interactive visualization tool allowed us to compare all communities at once, see www.cs.umd.edu/hcil/manynets for video demonstrations. All our tools are available for others to use. Our papers are also available at www.cs.umd.edu/hcil/non. In the longer term, the software tools and community success metrics we have developed will enable future interface designers and community managers to better understand and promote their communities.
