Thesis (M.A.)--Boise State University, 2009. / Includes bibliographical references (leaves 97-102).

Thesis (M.S.)--University of North Texas, May, 2009. / Title from title page display. Includes bibliographical references.

Thesis (M.A.)--Boise State University, 2009. / Title from t.p. of PDF file (viewed June 22, 2009). Includes bibliographical references (leaves 97-102).

Thesis (Ph.D.)--University of Texas at Dallas, 2008. / Includes vita. Accompanied audiodisc contains files for a variety of sounds. Includes bibliographical references (leaves 161-176)

Thesis (MFA)--Montana State University--Bozeman, 2009. / Typescript. Chairperson, Graduate Committee: Theo Lipfert. Includes bibliographical references (leaves 27-30).

Thesis--Auburn University, 2009. / Abstract. Vita. Includes bibliographical references (p. 35-37).

Virtual worlds and massively-multiplayer online games are rich sources of information about large-scale teams and groups, offering the tantalizing possibility of harvesting data about group formation, social networks, and network evolution. They provide new outlets for human social interaction that differ from both face-to-face interactions and non-physically-embodied social networking tools such as Facebook and Twitter. We aim to study group dynamics in these virtual worlds by collecting and analyzing public conversational patterns of users grouped in close physical proximity. To do this, we created a set of tools for monitoring, partitioning, and analyzing unstructured conversations between changing groups of participants in Second Life, a massively multi-player online user-constructed environment that allows users to construct and inhabit their own 3D world. Although there are some cues in the dialog, determining social interactions from unstructured chat data alone is a difficult problem, since these environments lack many of the cues that facilitate natural language processing in other conversational settings and different types of social media. Public chat data often features players who speak simultaneously, use jargon and emoticons, and only erratically adhere to conversational norms. Humans are adept social animals capable of identifying friendship groups from a combination of linguistic cues and social network patterns. But what is more important, the content of what people say or their history of social interactions? Moreover, is it possible to identify whether iii people are part of a group with changing membership merely from general network properties, such as measures of centrality and latent communities? These are the questions that we aim to answer in this thesis. The contributions of this thesis include: 1) a link prediction algorithm for identifying friendship relationships from unstructured chat data 2) a method for identifying social groups based on the results of community detection and topic analysis. The output of these two algorithms (links and group membership) are useful for studying a variety of research questions about human behavior in virtual worlds. To demonstrate this we have performed a longitudinal analysis of human groups in different regions of the Second Life virtual world. We believe that studies performed with our tools in virtual worlds will be a useful stepping stone toward creating a rich computational model of human group dynamics.

Thesis (Ph.D.)--Ohio University, March, 2010. / Title from PDF t.p. Includes bibliographical references.

The proliferation of the Internet and online-based social interactions has become an increasingly popular topic with communication scholars. The goal of this study was to explore how massively multi-player online role playing game (MMORPG) players make sense of and negotiate their online social interactions. This study (N = 292) examined how players of SecondLife and World of Warcraft evaluated their online relationships compared to their offline relationships and investigated how different levels of realism within different MMORPGs effected player's online experiences. The results indicated that players of SecondLife placed higher values of emotional closeness to their online relationships when compared to players of World of Warcraft and SecondLife was rated more real by its players than World of Warcraft. Results further indicated that players of SecondLife had higher levels of perceived online emotional closeness when compared to perceived offline emotional closeness. Implications of this study focus on developing a bottom up holistic profile of online game players as opposed to the current top down research model.

The management of online learning environments so that they are effective and efficient presents a significant challenge for institutions and lecturers due to the complexity of requirements in the learning and teaching domain. The use of 3D Multi User Virtual Environments (MUVEs) for education introduces a novel set of management challenges. MUVEs were designed to cater for entertainment and commercial needs and as such do not intrinsically support managed learning. When MUVEs are used for educational purposes, forming 3D Multi User Learning Environments (MULEs), user support for learning management becomes an important factor. This thesis highlights the importance of managed learning in MULEs. It proposes a coordinated approach which accommodates the existing education institutional infrastructure. The research has focused on two very widely used and closely compatible MUVEs, Second Life (SL) and OpenSim. The thesis presents system and user studies that have been carried out on these selected MUVEs. The findings reveal the challenges that academics and students can experience if they do not have sufficient knowhow to manage learning activities in SL/OpenSim. User guidance and training tools were then developed for supporting learning management strategies in the context of SL/OpenSim and demonstrated in exemplar use-case scenarios. The user support models and tools which were developed have been extensively evaluated for their usability and educational value using diverse participant groups. The results validate the efficacy of these contributions, defending the research thesis. These contributions can be used in future research on managing MUVE supported education.