Automated Discovery of Social Networks in Online Learning Communities

E-learning;Network Visualization;Online communities;Social Network Analysis;Text Mining

Gruzd, Anatoliy

关键词: E-learning;    Network Visualization;    Online communities;    Social Network Analysis;    Text Mining;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/11968/gruzd_anatoliy.pdf?sequence=2&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

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