In 2013, South Carolina implemented a multi-year program providing support services for pregnant and parenting teens. Local lead sites were responsible for coordinating service delivery in partnership with other multidisciplinary community-based organizations. We used social network theory and analyses (SNA) to examine changes in partnerships over time. Using two-stage purposeful sampling, we identified three lead sites and their self-reported community partners. We administered two web-based surveys grounded in social network theory that included questions about partnership relationships and organizational characteristics. We calculated selected whole-network measures (size, cohesion, equity, diversity). Following the Year 1 surveys, we reviewed our findings with the lead sites and suggested opportunities to strengthen their respective partnerships. Following the Year 3 surveys, we observed changes across the networks. Survey response rates were 91.5% (43/47) in Year 1 and 68.2% (45/66) in Year 3. By Year 3, the average network size increased from 15.6 to 20.3 organizations. By Year 3, one lead site doubled its measure of network cohesion (connectedness); another lead site doubled in size (capacity). A third lead site, highly dense in Year 1, increased in size but decreased in cohesion by Year 3. Innovative use of SNA findings can help community partnerships identify gaps in capacity or services and organizations needed to fulfill program aims. SNA findings can also improve partnership function by identifying opportunities to improve connectedness or reduce redundancies in program work. The ability of lead sites to strategically reconfigure partnerships can be important to program success and sustainability.

How do individual qualities of interest groups and group interactions influence public policy through the courts? This research is grounded in two primary assumptions: 1) neither are all amicus briefs (formal tool to lobby the court) equal, nor do amicus-filing organizations have the same attributes, and 2) the behavior of Supreme Court justices is shaped by the qualities of actors external to the court. Through advanced statistical techniques, and the tools of network analysis, I build on previous scholarship to provide a large-scale study of how the qualities of amicus brief cosigners, and their interaction within their advocacy network over time, bear on judicial politics. Making use of the total population of amicus-filling organizations to U.S. Supreme Court cases between 1945 and 2012, chapter 1 uses a dynamic network analysis to investigate the evolution of organizational identity and coalition behavior of interest groups based on the issue area they advocate for. Chapter 2 investigates the impact of the ideological composition of interest groups supporting the litigants on the justices’ vote. Chapter 3 analyzes how decision at the agenda-setting stage interacts with outside lobbying to influence the opinion-writing process on merit. The results provide a more comprehensive picture a more comprehensive picture of judicial lobbying; a crucial piece in the operation of the American democracy.

This study discovers sex differences in multiplex links on formal and informal networks of Swedish local elite. Elites are widely known to have an immense influence on a country’s politics and governance, and proportional representation of women in elite positions is an indicator of democratization and gender equality. Sweden has long been known for democratic and gender equal regulations, and women occupy more elite positions relative to other countries, yet they are still heavily underrepresented in the elite. Previous research on Swedish local elite revealed that women in the elite do not differ from their male peers in terms of local network properties on formal and informal networks; however, the circumstances on the multiplex links are unknown. In this study, multiplexity approach is adopted as it is known for allowing to capture social processes in social network analysis, which could otherwise be overlooked. The formal and informal networks of the community elite from four mid-sized municipalities in Västra Götaland region in Sweden are transformed into multiplex networks, and they were analyzed for local network configurations by using exponential random graph model (ERGM) estimation method. The findings showed that women in the community elite tend to have more multiplex relationships than men; however, they significantly lack valuable brokerage positions on the multiplex level compared to men. Male closure on the multiplex level was found to be higher than females at a partially significant rate, and gender-based homophily on multiplex networks was not found to be statistically significant. One implication of the study is women’s position and integration in the community elite do not appear identical to men’s, and women’s access to social capital in the elite networks is more constrained than it was presumed previously. Another implication is that special attention should be paid to multiplexity in social network analysis research, as it is a valuable tool for improving the apprehension of social mechanisms.

In the post-genomic era, there is a dire need for tools to perform metabolic analyses that include the structural, functional, and regulatory analysis of metabolic networks. This need arose because of the lag between the two phases of metabolic engineering, namely, synthesis and analysis. Molecular biological tools for synthesis like recombinant DNA technology and genetic engineering have advanced a lot farther than tools for systemic analysis. Consequently, bioinformatics is poised to play an important role in bridging the gap between the two phases of metabolic engineering, thereby accelerating the improvement of organisms by using predictive simulations that can be done in minutes rather than mutant constructions that require weeks to months. In addition, metabolism occurs at a rapid speed compared to other cellular activities and has two states, dynamic state and steady state. Dynamic state analysis sheds more light on the mechanisms and regulation of metabolism than its steady state counterpart. Currently, several in silico tools exist for steady-state analysis of metabolism, but tools for dynamic analysis are lacking. This research focused on simulating the dynamic state of metabolism for predictive analysis of the metabolic changes in an organism during metabolic engineering. The goals of this research were accomplished by developing two software tools. Metabolome Searcher, a web-based high throughput tool, facilitates putative compound identification and metabolic pathway mapping of mass spectrometry data by applying genome-restriction. The second tool, DynaFlux, uses these compound identifications along with time course data obtained from a mass spectrometer in conjunction with the pathways of interest to simulate and estimate dynamic-state metabolic flux, as well as to analyze the network properties. The features available in DynaFlux are: 1) derivation of the metabolic reconstructions from Pathway Tools software for the simulation; 2) automated building of the mathematical model of the metabolic network; 3) estimation of the kinetic parameters, KR, v, Vmaxf, Vmaxr, and Kdy, using hybrid-mutation random-restart hill climbing search; 4) perturbation studies of enzyme activities; 5) enumeration of feasible routes between two metabolites; 6) determination of the minimal enzyme set and dispensable enzyme set; 7) imputation of missing metabolite data; and 8) visualization of the network.

Globalization impacts the Architecture, Engineering and Construction (AEC) industry; customers in the AEC industry are seeking lower costs, faster construction schedules and higher quality services. In order to keep up with the changing demand and to stay competitive in the global AEC industry, firms are forming joint ventures and outsourcing design and services work.  As a result, these new trends in the AEC industry require the collaboration of widely dispersed and diverse project workers and companies.  Accordingly, it becomes increasingly important to understand the impact of diversity on performance.  In this sense, the initial aim of this study was to find empirical evidence on how differences in national culture and language may affect performance in Global Project Networks (GPNs).  According to the results of the first experiment comparing the performance of multi-cultural versus mono-cultural simulated project networks over time, I found cultural and linguistic diversity to have a negative impact on initial performance. However, culturally and linguistically diverse project networks studied achieved better adaptation performance that has long term advantages. Even though GPNs have long term performance benefits, bringing the widely dispersed project participants together is costly.  Therefore, firms are seeking ways to employ collaboration technologies to bring together the project participants.  Little research exists to examine how to increase the efficiency of GPNs that collaborate using technologies such as virtual workspaces to perform design work.  In order to examine collaboration in GPNs utilizing virtual workspaces, I conducted two experiments.  In the first study, I investigated the formation and the maintenance of Transactive Memory Systems (TMSs) and cohesive subgroups as a proxy for performance in two facilitated and two non-facilitated global virtual project networks.  I found a negative impact on collaboration effectiveness when process facilitators engaged in content facilitation in virtual project networks, which restricts the establishment of TMSs. The findings of the first study revealed inappropriate ways of facilitating GPNs collaborating in virtual workspaces, which motivated the second study.  In the second experiment, I observed two global and two domestic virtual project networks that were appropriately facilitated.  I examined the interactions between network members in order to identify whether significant differences between the collaboration approaches of global and domestic virtual project networks exist. Facilitators were utilized more frequently in global networks, particularly in the early stages of collaboration. Boundary spanning visualization technologies within the virtual workspace were also utilized more frequently by the global network members; however, this was due more to the spatial richness of the task than the maturity of the collaboration. The overall findings have significant implications in improving the effectiveness of global project network collaborations in virtual workspaces. / Ph. D.

In recent years, disinformation circulating the internet and especially social media has become a widespread concern. The urgency of the fake news problem lies in the fact that decisions that are taken on false or misleading information risk impacting democratic processes negatively. This is especially true during a global health crisis when the misinformation in question concerns scientific facts and informs the way people act in society. Focusing on the relational aspect of fake news, new insight and hypothesis generation can be explored with a relatively novel method, social network analysis. This research provides with an example of the method applied to political problems by analysing the misinformation and fact-checking diffusion network on the Italian Twitterverse during the second wave of COVID19. The network shows a tight core of misinformation and a peripheral fact-checking region approximating a spanning tree. Although some levels of polarization are observed, the resulting network shows no evidence of echo chambers that hinder interaction between the misinformation and the fact-checking clusters. Actor-level analysis revealed that the majority of the users interacting in the network are humans and that influential and active users share misinformation only. The findings of this work are presented to show how network analysis can contribute both mitigation strategies in particular and to social and political sciences research in general.

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"Where You Sit Matters: Diplomatic Networks and International Conflict" examines how a state's structural position within diplomatic networks influences its foreign policy behaviors, particularly in the domain of international security. Despite the established understanding in International Relations (IR) that relationships among countries matter, there is little empirical knowledge on what exactly the complicated web of those relationships looks like and how it impacts state behavior. Much IR literature tends to focus only on dyadic or multilateral relationships and treat networks as background, which has left a gap in our understanding of how the structures of international networks affect international outcomes. To address this gap, my dissertation uses network analysis and a variety of statistical methods to reveal key structures of diplomatic networks and examine their impacts on a state's foreign policy behavior. My argument extends in three directions. The first part uses a large-n, cross-sectional analysis to examine the impacts of a state's broker position within diplomatic networks on its decision to initiate and escalate militarized interstate disputes (MIDs). By using the rare events logit and Heckman selection models, I find that occupying a broker position in diplomatic networks increases a state's decision to initiate MIDs over the nearly 200-year period from 1817 to 2001; its marginal impact is nearly twice that of military capability. The second part employs a separable temporal exponential random graph model (STERGM) to examine how key structures of diplomatic networks influence a state's decision to terminate diplomatic ties. My findings show that the breakdown of diplomatic ties is not a rare event and network dynamics play a role in terminating ties: states take cues from other countries in the network to decide whether or not to terminate diplomatic ties. The last part uses a community detection method, specifically a link communities method, to reveal latent communities of the diplomatic network and identify key countries that belong to multiple communities. I find that the diplomatic network resembles a hierarchical structure in that diplomatic communities tend to overlap; only a small number of major powers simultaneously belong to multiple communities and few communities are independent from those major powers.

Tuberculosis (TB) is one of the most deadly diseases worldwide. In the United States, TB disproportionately affects foreign-born individuals, individuals living in congregate settings, people with human immunodeficiency virus, and people who use illicit drugs. In 2005, a large homeless shelter outbreak in San Joaquin County resulted in 67 individuals diagnosed with TB with links to a homeless shelter. It is hypothesized that by using bed analysis to identify contacts that have been exposed to TB during this outbreak will allow for better identification of exposed high-risk individuals than screening alone. Demographics, exposure, screening, and QuantiFERON-Tuberculosis results were analyzed using bed assignments from the homeless shelter database and data from a homeless shelter screening (HSS) program. Individuals diagnosed with active TB disease were on average more likely to be identified through bed analysis than HSS, 95.08% versus 59.02%. Utilizing both bed analysis and HSS allows for improvement of identification and continuous testing of individuals exposed to TB.

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