Automated Discovery of Social Networks in Online Learning Communities

As a way to gain greater insights into the operation of online communities, this dissertation applies automated text mining techniques to text-based communication to identify, describe and evaluate underlying social networks among online community members. The main thrust of the study is to automate the discovery of social ties that form between community members, using only the digital footprints left behind in their online forum postings. Currently, one of the most common but time consuming methods for discovering social ties between people is to ask questions about their perceived social ties. However, such a survey is difficult to collect due to the high investment in time associated with data collection and the sensitive nature of the types of questions that may be asked. To overcome these limitations, the dissertation presents a new, content-based method for automated discovery of social networks from threaded discussions, referred to as ‘name network’. As a case study, the proposed automated method is evaluated in the context of online learning communities. The results suggest that the proposed ‘name network’ method for collecting social network data is a viable alternative to costly and time-consuming collection of users’ data using surveys. The study also demonstrates how social networks produced by the ‘name network’ method can be used to study online classes and to look for evidence of collaborative learning in online learning communities. For example, educators can use name networks as a real time diagnostic tool to identify students who might need additional help or students who may provide such help to others. Future research will evaluate the usefulness of the ‘name network’ method in other types of online communities.

Planning across differences: collaborative planning processes for the California Central Valley's future

This dissertation examines the intersections between difference, participation, and planning processes. Rooted in scholarly conversations about deliberative democracy, collaborative planning, and nonprofit organizations in civil society, this research considers how planning practitioners can better plan across difference. Through case study research, this dissertation examines a collaborative planning process conducted by a nonprofit organization. Unlike more conventional participatory planning processes, the organization utilized scenario planning. Exercising their position in civil society, participation in the process was not open to all community members and the organization carefully selected a diverse set of participants. Findings from this research project indicate that this process, by moving away from a strict definition of rational discourse, focusing on multiple futures as opposed to a single, utopian future, and deliberately bringing together a broad cross-section of community members allowed for participants to speak freely and learn from one another’s perspectives and experiences. Experiences of process participants also demonstrate the degree to which cultural backgrounds shape participation in and expectations of planning processes. While there remains no clear answer in how to represent and respond to cultural differences in planning processes, the experiences of the organization, program staff, and community participants help scholars and practitioners move closer to planning across differences.