Much structured data of scientific interest can be represented as networks, where sets of nodes or vertices are joined together in pairs by links or edges. Although these networks may belong to different research areas, there is one property that many of them do have in common: the network community structure, which means that there exists densely connected groups of vertices, with only sparser connections between groups. The main goal of community mining is to discover these communities in social networks or other similar information network environments. We face many deficiencies in current community structure discovery methods. First, one similarity metric is typically applied in all networks, without considering the differences in network and application characteristics. Second, many existing methods assume the network information is fully available, and one node only belongs to one cluster. However, in reality, a social network can be huge thus it is hard to access the complete network. It is also common for social entities to belong to multiple communities. Finally, relations between entities are hard to understand in heterogeneous social networks, where multiple types of relations and entities exist. Therefore, the thesis of this research is to tackle these community mining problems, in order to discover and evaluate community structures in social networks from various aspects.

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In recent decades, political parties espousing extreme nationalist, xenophobic, and even outright racist platforms have enjoyed variable success in national elections across Europe. While a vibrant research literature has sought to better understand the sources of support for such parties, remarkably little attention has been paid to the interplay between parties and the broader social networks of extremism in which they are embedded. To remedy this deficiency, the present study examines the relations between far-right parliamentary parties and their extra-parliamentary networks. One level of analysis tests whether there is a relationship between a party’s position within a network and its sustainability. Social network analysis is employed to assess the nature and structure of ties between Belgian organizations online. In addition, systematic textual analysis of website content is used to determine how a party’s ideological position within the network impacts its sustainability. The second level of analysis is a qualitative study based on in-depth interviews with members of Flemish nationalist organization in order to better understand how actors experience social networks. Evidence suggests that the most sustainable parties are those that have dense connections with other nationalist organizations. Mapping relations between far-right parties that compete openly within the rules of institutionalized democracy and their wider social networks can provide important policy-relevant insight into contemporary challenges posed by illiberal forces.

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Thesis advisor: Patrick McQuillan / The challenges facing our communities are complex, interconnected, and urgent (Kania & Kramer, 2011). Recognizing these challenges, policy makers, funders, and practitioners are turning to social partnerships as a promising strategy for community and educational change (Bess, 2015; Henig et al., 2015). Social partnerships involve the joining together of organizations from across sectors of society to tackle social problems (Crane & Seitanidi, 2014). The underlying premise of the Promise Neighborhoods program, one such social partnership, is that providing access to resources, services, and supports in a comprehensive manner will have the greatest effect on educational and community outcomes (U.S. Department of Education, 2018). This study seeks to shed light on the process of initiating and implementing a social partnership. In this study the author employed a two-phased, mixed methods design using social network analysis and interviews with organizational representatives to examine the network structures of communication and collaboration within one Promise Neighborhoods initiative: the Boston Promise Initiative. The sample for the social network analysis consisted of 33 individuals from 27 partner organizations. Further, follow-up interviews with 11 individuals were held to understand how network structures and processes might impact educational and community change. Findings from the social network analysis and qualitative interviews reveal networks of communication and collaboration rooted in a deep history of place-based change efforts, facilitating access to network resources and social capital among partner organizations. The findings highlight the importance of recognizing both challenges and opportunities of partnering with schools. Further, the findings highlight the importance of a lead organization’s ability to attend to both technical processes, such as facilitating communication among partners, and cultural processes, such as negotiating organizational identity. Taken together, the findings from this study point to the complex nature of cross-sector collaboration and identify structural factors and network processes that may impact the success of the efforts. By better understanding the structure and processes inherent in social partnerships, organizations can be better supported as they develop and implement cross-sector initiatives aimed at making meaningful change in their communities. / Thesis (PhD) — Boston College, 2018. / Submitted to: Boston College. Lynch School of Education. / Discipline: Teacher Education, Special Education, Curriculum and Instruction.

Interdisciplinary Research (IDR) has received a lot of attention from academics, policy-makers, and decision-makers alike. RCUK invests £3 billion in research grants each year (RCUK 2017); half of the grants are provided to investigators who hail from different departments. There is mounting awareness of the challenges facing IDR, and a large body of literature trying to establish how IDR can be analysed (Davidson 2015, Yegros-Yegros, Rafols et al. 2015). Of these, the majority have been qualitative studies and it has been noticed that there is a distinct lack of quantitative studies that can be used to identify how to enable IDR. The literature shows that many of the barriers to IDR can be classified as either cultural or administrative (Katz and Martin 1997, Cummings and Kiesler 2005, Rafols 2007, Wagner, Roessner et al. 2011), neither of which are easily changed over a short period of time. The perspective taken in this research is that change can be affected by enabling the individuals who conduct IDR. Herein lies the main challenge; how can these future leaders of IDR be identified so that they can be properly supported. No existing datasets were deemed suitable for the purpose, and a new dataset was created to analyse IDR. To isolate dynamics within an organisation, hard boundaries were drawn around research-organisations. The University of Bath journal co-authorship dataset 2000-2017 was determined to be suitable for this purpose. From this dataset a co-authorship network was created. To analyse this, established models from literature were adapted and used to identify differences in disciplinary and interdisciplinary archetypes. This was done through a correlational study. No statistically significant differences between such author archetypes were found. It was therefore concluded that an alternative approach was necessary. By adapting the networks framework to account for different types of links between edges, a multilayer perspective was adopted. This resulted in a rank-3 tensor, node-aligned framework being proposed, allowing disciplines to be represented in the network. By using this framework to construct the University of Bath multiplex co-authorship network, an exemplar structure was established through use of a series of proposed structural metrics. A growth model was proposed and successfully recreated the structure and thereby uncovered mechanics affecting real-world multiplex networks. This highlighted the importance of node entities and the layer closeness centrality. This implies that it is very difficult to carry over benefits across disciplines, and that some disciplines are better suited to share and adapt knowledge than others. The growth model also allowed an analytical expression for the rate of change of disciplinary degree, thereby providing a model for who is most likely to enable and sustain IDR.

Information networks represent relations in data, relationships typically ignored in iid (independent and identically distributed) data. Such networks abound, like coauthorships in bibliometrics, cellphone call graphs in telecommunication, students interactions in Education, etc. A large body of work has been devoted to the analysis of these networks and the discovery of their underlying structure, specifically, finding the communities in them. Communities are groups of nodes in the network that are relatively cohesive within the set compared to the outside. This thesis proposes Top Leaders, a fast and accurate community mining approach for both weighted and unweighted networks. Top Leaders regards a community as a set of followers congregating around a potential leader and works based on a novel measure of closeness inspired by the theory of diffusion of innovations. Moreover, it proposes Meerkat-ED, a specific and practical toolbox for analyzing students interactions in online courses. It applies social network analysis techniques including community mining to evaluate participation of students in asynchronous discussion forums.

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Policing in America has lost more officers to suicides than line of duty deaths over the past four years. As the gatekeepers to the criminal justice system, the well-being of officers is critical as unhealthy police using poor coping strategies to handle their stress can lead to a multitude of negative consequences for the communities they serve, their departments, their fellow officers, and themselves. While the technology of policing is quickly advancing, the routine duties of officers remain stressful. This stress requires officers to use effective coping strategies to deal with it, but the traditional subculture of policing promotes maladaptive, rather than adaptive, coping strategies. To understand how the subculture influences police and the coping strategies they use, research must understand the socialization process of recruits entering the job. The current research seeks to understand how police recruits are socialized into the police subculture and how this affects the coping strategies they use to deal with the stressors they will confront on the job. The research analyzes how the network position of recruits influences their adoption of the police subculture and how this, in turn, affects their development of coping strategies. Recruits were surveyed three times during their academy training to examine the transitioning and socialization that occurs throughout the police academy. Results reveal that networks affect the adoption of the police subculture by recruits and this socialization process impacts the development of coping strategies by recruits. Findings highlight the need for future work to continue the longitudinal research approach to examine how the networks change once recruits complete their field training and probationary period. / Doctor of Philosophy / Police officers are engaged in an occupation that induces a vast amount of stress, leading to burnout and poor coping strategies. Blue H.E.L.P. began tracking the suicide rates of law enforcement and found that officers are dying more often by their own hands than in line of duty deaths. We have also seen growing tensions between police and communities, further leading to lower retention rates of current officers. The current study seeks to understand how police recruits are trained to endure the stress of their occupation. Policing is comprised of a unique occupational culture that creates solidarity among its members, which can influence how officers learn to utilize coping mechanisms. The current research examines how new police recruits fit into this occupational culture and how this affects their coping strategies over time. Results show that how new recruits are socialized into the occupational culture matter in terms of how they learn to cope with their job. Understanding how new recruits are taught to cope is imperative to destigmatize the notion of well-being to train healthier officers and to potentially lower suicide rates among our nation's law enforcement.

Yes / The growing body of published e-government literature highlights the importance of e-government in society and the need to make sense of e-government by academia. In order to understand the future of e-government, it is important to understand the research that has been conducted and highlight the issues and themes that have been identified as important by empirical study. This paper analyses the corpus of e-government research published from 2000 to 2013 using Bibliometric and Social Network Analysis (SNA) methods to develop an intellectual structure of e-government research. Factor analysis, multidimensional scaling and centrality measurement are also applied to the e-government dataset using UCINET to identify the core influential articles in the field. This study identifies three core clusters of e-government research that centre around (i) e-government development models (ii) adoption and acceptance of e-government, and (iii) e-government using social media and highlights areas for future research in the field. Discover the world's research