Recent advances in information technologies provide a unique opportunity for sharing knowledge free from constraints of time and place. One application area is Internet-based learning where members of virtual groups are separated by location, and are challenged by a collaborative project. In this research we investigate the developmental patterns of such groups, and address how trust may shape and be shaped by the virtual groups¡¦ development. Twenty-five groups in a cyber-university participate in our study. Our findings suggested the development of virtual groups was characterized by three stages: dependency and flight, fight and pair, and work. In addition, virtual group members initially imported trust rather than developed trust. Calculus-based trust, knowledge-based trust and identification-based trust coexisted and co-evolved over time. Finally, there appeared to be a reciprocal relationship between trust and group development.

Virtual group therapy offers multiple unique advantages to improving access to mental health care for Canadian youth and families. However, virtual environments may hinder the development of the type of relationships within groups that promote positive treatment outcomes. The present study explores the extent to, and ways in which, service providers working in the youth and family mental health sector in Eastern Ontario adapt to the unique characteristics of virtual environments in order to communicate effectively and develop therapeutic relationships. Secondary quantitative and qualitative data were analyzed using a mixed-methods design. Survey responses (n = 58) and interview recordings (n =12) collected from service providers involved in the delivery of virtual groups for youth and families in response to COVID-19 were analyzed using a concurrent triangulation design. Descriptive statistics indicate service providers achieved moderate satisfaction regarding their ability to communicate and develop relationships within virtual groups, and that this ability was perceived as approximating in-person processes. Thematic analysis suggests that while virtual group environments involve unique challenges and and elevated complexity, facilitators adapt to virtual delivery by both employing diverse strategies and accepting certain limitations. The present study suggests that the unique challenges and complexities involved in virtual group-based therapy need not deter the implementation of virtual groups as a means of better addressing the mental health needs of Canadian youth and families.

In this study, an online movie recommendation engine that serves on Facebook is developed in order to evaluate social circle eects on user preferences in a trust-based environment. Instead of using single-user profiles in the social environment identification process, virtual group profiles that present common tastes of the social environments, are formed to achieve a successful social circle analysis and innovative suggestions. Recommendations are generated based on similar social circles and based on social circles of similar users separately and their results are evaluated. Pure collaborative filtering is applied to emphasize the influence of social environment characteristics.

In today's global competitive environment, many organizations utilize virtual workgroups to overcome geographic and organizational boundaries. Research into their dynamics has received the attention of scholars within multiple disciplines, and the potential for an integrative approach to the study of virtual workgroups exists. This dissertation is a first step towards such an approach. The primary aim of this research is to examine antecedent and contextual factors that affect the emergence and effectiveness of leaders in virtual workgroups. To achieve this aim, an integrative model assembled from theory and empirical findings in leadership, management, social identity, and communications research is posited. Hypothesized relationships depicted in the model identify key dispositional and contextual variables linked to leader emergence, member behavior, and leader effectiveness within virtual workgroups. This study employed a nonexperimental research design, in which leader emergence and social identity manifest as naturally occurring phenomena. Data collection occurred via two web-based surveys administered at different points in time. Hypothesized relationships were tested utilizing correlational and hierarchical moderated multiple regression analyses. The findings of this dissertation suggest that traits, such as personality and cognitive ability, are not associated with leader emergence in virtual workgroups. In addition, the results indicate that the exhibition of relationship-oriented leader behaviors enhances group identity. In turn, identification is associated with increases in perceptions of leader effectiveness and decreases in counterproductive behavior exhibited by group members. This dissertation exposes an important limitation to the application of trait leadership theory. It also demonstrates the importance of relationship-oriented behavior and social identity in virtual contexts. Further, it advances an integrative theoretical model for the study of virtual workgroup phenomena. These contributions should assist and inform other researchers, as well as practitioners, interested in leadership and group member behavior in virtual workgroups.

M. Tech. (Department of Information and Communication Technology, Faculty of Applied and Computer Sciences), Vaal University of Technology. / Since their emergence in the 1990’s, recommendation systems have transformed the intelligence of both the web and humans. A pool of research papers has been published in various domains of recommendation systems. These include content based, collaborative and hybrid filtering recommendation systems. Recommendation systems suggest items to users and their principal purpose is to increase sales and recommend items that are predicted to be suitable for users. They achieve this through making calculations based on data that is available on the system. In this study, we give evidence that the research on group recommendation systems must look more carefully at the dynamics of group decision-making in order to produce technologies that will be more beneficial for groups based on the individual interests of group members while also striving to maximise satisfaction. The matrix factorization algorithm of collaborative filtering was used to make predictions and three movie recommendation for each and every individual user. The three recommendations were of three highest predicted movies above the pre-set threshold which was three. Thereafter, four virtual groups of varied sizes were formed based on four highest predicted movies of the users in the dataset. Plurality voting strategy was used to achieve this. A publicly available dataset based on Group Recommender Systems Enhanced by Social Elements, constructed by Lara Quijano from the Group of Artificial Intelligence Applications (GIGA), was used for experiments. The developed recommendation system was able to successfully make individual movie recommendations, generate virtual groups, and recommend movies to these respective groups. The system was evaluated for accuracy in making predictions and it was able to achieve 0.7027 MAE and 0.8996 RMSE. This study was able to recommend to virtual groups to enable social network group members to engage in discussions of recommended items. The study encourages members in engaging in similar activities in their respective physical locations and then discuss on social network.