On September 18, 2015, the U.S. Environmental Standards Agency (EPA) filed a Notice of Violation of the Clean Air Act to the Volkswagen Group regarding software used to intentionally deceive the EPA’s emissions tests. Social media is an efficient way for organizations to release information and respond quickly during a crisis. Not only are organizations posting on social media sites, but consumers are increasingly turning to social media sites, such as Twitter, during crises to share information and opinions. The VW crisis may impact Germany’s nation brand, as predicted by more recent country-of-origin literature. The country-of-origin effect occurs when the reputation of a country impacts consumer perceptions of products produced by that country. When consumers had favorable perceptions of a country, Xu and Wu (2015) found the country’s products were more likely to receive positive after-crisis reactions. German products are considered to be of high quality. “So, in the case of Germany, the development of its national brand identity is an integral part of the growth and development of its exports, the ‘Made in Germany’ label that has a world-class reputation,” (Joseph, 2014, p. 4). A content analysis was performed to examine the international conversation on Twitter through the analysis of tweets that included at least one of the following hashtags: #VWGate, #DieselGate, #VWscandal or #Volkswagenscandal.

M.Sc. (Mathematics) / In Chapter 1, we consider the relevant theory pertaining to graphs and digraphs that will be used in the study of flows in networks. Warshall’s algorithm for reachability is also considered since it will allow us to ascertain whether some paths exist in some instance. In Chapter 2, we explore flows and cuts in networks. We define the basic concepts of source, sink, intermediate vertices, capacity, costs and lower-bounds. Feasible flows are defined, as well as the value of a flow. Cuts in capacitated networks are explored and further theory relating the value of a flow and cuts is given. We considered the problem of determining a maximal flow. In particular, we consider augmentations of the flow—this allows us to give a characterization of a maximal flow. The important Max-flow Min-cut theorem is also considered. After having explored the relevant theory, we move on to methods of finding a maximal flow for a given s-t network that has a capacity on each of its arcs. Firstly, we consider zero-one and unit-capacity networks since these play a role in the applications of maximal flows in Chapter 4. We, then, compile the relevant theory and algorithms in order to implement two augmenting path finding algorithms.

Estuaries are some of the most productive yet threatened ecosystems in the world. Despite their importance they face significant threats through changes to river flow, eutrophication, rapid population growth long the caost and harvesting of natural resources. A number of international studies have been conducted investigating the structure and functioning of an array of ecosystems using ecological network analysis. Energy flow networks have been contsructed for coastal, lagoonal, intertidial and, most notably, permantently open estuaries. Despite the valualble insights contributed by these and other studies, a lack of information on the majority of estuarine ecosystems exists.

Studies of adaptive governance in social-ecological systems have identified common features that assist social actors in responding to environmental pressures. Among these features, multiple sources of ecological knowledge, trust, and networks between actors have been highlighted as properties that contribute to successful governance arrangements. However, studies in adaptive governance have also been critiqued using a political ecology approach. This is due to their under-theorization of political elements that can constrain or promote the formation of the features of adaptive governance. In particular, power dynamics between actors and the subsequent privileging of one source of knowledge over another might have an effect on governance arrangements. In China, environmental degradation is a serious issue. The Qinhuai River, located in the city of Nanjing, has experienced significant ecological decline over the last 30 years as urbanization pressures on the system increased. Over the same period, China has undergone changes in state-society relations, including allowing the formation of NGOs. Since the turn of the millennium, several NGOs have begun working on issues related to the Qinhuai River, including raising awareness and producing information on the environment. This study examines the features of adaptive governance in a critical light by situating them in the local political context of China. The relationship between NGOs, fishers who use the Qinhuai River and government are examined using Social Network Analysis and semi-structured interviews in order to understand the production of information, networking and trust between these actors. It is shown that the existing arrangements to include NGOs and fishers in the river’s governance activities are guided by a corporatist system of state-sanctioned representation. This is not conducive to adaptive governance arrangements, despite the increasing existence of ENGO networks and new sources of knowledge over the last decade. It is thus important that studies of adaptive governance take steps to contextualize their findings within the local political climate.

Increasing collaborative working between GPs and community pharmacists has recently become a high priority for the NHS. Previous research suggests that interaction is limited and problematic between the two professions, forming a barrier to service provision. This PhD aimed to explore the level, nature and process of interaction between GPs and community pharmacists, using a social network analysis approach.The study focused on four geographically different case study areas and 90 GPs and community pharmacists participated in total. A two-stage design was adopted. Firstly data were collected through a network questionnaire and analysed using social network analysis. Secondly, qualitative interviews were conducted to provide narrative to the network findings and analysed using the framework approach.The nature of contact was characterised as mostly indirect through brokers, de-personalised and non-reciprocal and seemingly at odds with collaborative behaviour. A misalignment in responses pointed to asymmetry in the relationship, representing little commonality, knowing and understanding of each other. Through social network analysis, individuals and dyads in possession of strong ties were identified. Strong ties were not the norm and were characterised by more personalised forms of reciprocal contact. Qualitative interviews provided insight into the processes of interaction between the two professional groups. An approach to the interaction, which involved pharmacists tactically managing the potential conflict in the interaction through use of deferential and sometimes subservient behaviour, was conceptualised as the ‘pharmacist-GP game’. Those pharmacists with strong ties to GPs also, at times, adopted aspects of this approach but also attempted to set themselves apart from other pharmacists in order to develop and maintain their strong ties with GPs. However, possession of strong ties did not always lead to capitalisation, and the benefits of possessing these were often viewed as efficiency and convenience gains rather than anything more wide-reaching. Often, more isolated GPs and pharmacists did not view strong ties as a necessity, with the benefits of these not considered rewarding enough for the time and effort required to achieve them. This effort-reward conflict was identified as an important constraint faced by GPs and pharmacists in relation to transforming these loose connections into more integrated networks. Other micro and macro level constraints were also identified and a series of accompanying recommendations made for future practice and research.

This dissertation focuses on the performance analysis of multiclass open queueing networks using semi-martingale reflecting Brownian motion (SRBM) approximation. It consists of four parts. In the first part, we derive a strong approximation for a multiclass feedforward queueing network, where jobs after service completion can only move to a downstream service station. Job classes are partitioned into groups. Within a group, jobs are served in the order of arrival; that is, a first-in-first-out (FIFO) discipline is in force, and among groups, jobs are served under a pre-assigned preemptive priority discipline. We obtain an SRBM as the result of strong approximation for the network, through an inductive approach. Based on the strong approximation, some procedures are proposed to approximate the stationary distribution of various performance measures of the queueing network. Our work extends and complements the previous work done on the feedforward queueing network. The numeric examples show that the strong approximation provides a better approximation than that suggested by a straightforward interpretation of the heavy traffic limit theorem. In the second part, we develop a Brownian approximation for a general multiclass queueing network with a set of single-server stations that operate under a combination of FIFO (first-in-first-out) and priority service disciplines and are subject to random breakdowns. Our intention here is to illustrate how to approximate a queueing network by an SRBM, not to justify such approximation. We illustrate through numerical examples in comparison against simulation that the SRBM model, while not always supported by a heavy traffic limit theorem, possesses good accuracy in most cases, even when the systems are moderately loaded. Through analyzing special networks, we also discuss the existence of the SRBM approximation in relation to the stability and the heavy traffic limits of the networks. In most queueing network applications, the stationary distributions of queueing networks are of great interest. It becomes natural to approximate these stationary distributions by the stationary distributions of the approximating SRBMs. Although we are able to characterize the stationary distribution of an SRBM, except in few limited cases, it is extremely difficult to obtain the stationary distribution analytically. In the third part of the dissertation, we propose a numerical algorithm, referred to as BNA/FM (Brownian network analyzer with finite element method), for computing the stationary distribution of an SRBM in a hypercube. SRBM in a hypercube serves as an approximate model of queueing networks with finite buffers. Our BNA/FM algorithm is based on finite element method and an extension of a generic algorithm developed in the previous work. It uses piecewise polynomials to form an approximate subspace of an infinite dimensional functional space. The BNA/FM algorithm is shown to produce good estimates for stationary probabilities, in addition to stationary moments. This is in contrast to the BNA/SM (Brownian network analyzer with spectral method) developed in the previous work, where global polynomials are used to form the approximate subspace and they sometime fail to produce meaningful estimates of these stationary probabilities. We also report extensive computational experiences from our implementation that will be useful for future numerical research on SRBMs. A three-station tandem network with finite buffers is presented to illustrate the effectiveness of the Brownian approximation model and our BNA/FM algorithm. In the last part of the dissertation, we extend the BNA/FM algorithm to calculate the stationary distribution of an SRBM in an orthant. This type of SRBM arises as a Brownian approximation model for queueing networks with infinite buffers. We prove the convergence theorems which justify the extension. A three-machine job shop example is presented to illustrate the accuracy of our extended BNA/FM algorithm. In fact, this extended algorithm is also used in the first two parts of this dissertation to analyze the performance of several queueing network examples and it gives fairly good performance estimates in most cases. / Business, Sauder School of / Graduate

Main thesis objective is in social network analysis. Theoretic will describe their origin, development and circumstances under which certain social networks were built. Part with analysis will concern in how to compete with business rivals using CI and will search techniques for proper facebook usage as a company's CI tool by rating of chosen fan facebook pages.

Characteristically, propagation of news on the Internet is a rather complex scenario. Its comprehensive understanding requires a consideration of diverse facets such as audience, problem domain, channel and type of news being propagated. My dissertation focuses on the understanding of propagation of a specific type of news- news articles, on a particular subset of the Internet, the social media. While a number of studies have looked into the phenomenon of propagation in social media, fewer of these have examined the propagation of content, specifically news articles, published by news provider websites. My dissertation presents a set of network theory based methodologies to extract and analyze various implicit propagation networks formed as a result of news article sharing on Twitter. These methodologies cover aspects related to users' article sharing behavior, influence of the news provider's social media accounts, role of followers and similarities between propagation networks of news providers. Furthermore, it also includes useful inferences derived about the news article propagation phenomenon by using a population sized data sampled from Twitter over a nine-month period. It expands on the inferences from my published works and the challenges identified in the area of news article consumption and distribution on the Internet. My dissertation intends to provide important guidelines for researchers and organizations studying social media related phenomena to derive insights about customer behavior. From the perspective of online news consumption and distribution, my study has important implications for the audience's preference of news content delivery. It also facilitates news providers to gauge their performance on social media and for news editors to help develop editorial policies tailored for an online consumer base. Finally, my dissertation presents an extensive set of network based models and methodologies that can enrich the applied network science discipline.

<p>Care of patients with chronic conditions is complicated and usually includes large number of healthcare providers. Understanding the team structure and networks of healthcare providers help to make informed decisions for health policy makers and design of wellness programs by identifying the influencers in the network. This work presents a novel approach to assess the collaboration of healthcare providers involved in the care of patients with chronic conditions and the impact on patient outcomes. </p> <p>In the first study, we assessed a patient population needs, preventive service utilization, and impact of an onsite clinic as an intervention on preventive service utilization patterns over a three-year period. Classification models were developed to identify groups of patients with similar characteristics and healthcare utilization. Logistic regression models identified patient factors that impacted their utilization of preventive health services in the onsite clinic vs. other providers. Females had higher utilizations compared to males. Type of insurance coverages, and presence of diabetes/hypertension were significant factors that impacted utilization. The first study framework helps to understand the patient population characteristics and role of specific providers (onsite clinic), however, it does not provide information about the teams of healthcare providers involved in the care process. </p> <p>Considering the high prevalence of diabetes in the patient cohort of study 1, in the second study, we followed the patient cohort with diabetes from study 1 and extracted their healthcare providers over a two-year period. A framework based on the social network analysis was presented to assess the healthcare providers’ networks and teams involved in the care of diabetes. The relations between healthcare providers were generated based on the patient sharing relations identified from the claims data. A multi-scale community detection algorithm was used to identify groups of healthcare providers more closely working together. Centrality measures of the social network identified the influencers in the overall network and each community. Mail-order and retail pharmacies were identified as central providers in the overall network and majority of communities. This study presented metrics and approach for assessment of provider collaboration. To study how these collaborative relations impact the patients, in the last study, we presented a framework to assess impacts of healthcare provider collaboration on patient outcomes. </p> <p>We focused on patients with diabetes, hypertension, and hyperlipidemia due to their similar healthcare needs and utilization. Similar to the second study, social network analysis and a multi-scale community detection algorithm were used to identify networks and communities of healthcare providers. We identified providers who were the majority source of care for patients over a three-year period. Regression models using generalized estimating equations were developed to assess the impact of majority source of care provider community-level centrality on patient outcomes. Higher connectedness (higher degree centrality) and higher access (higher closeness centrality) of the majority source of care provider were associated with reduced number of inpatient hospitalization and emergency department visits. </p> <p>This research proposed a framework based on the social network analysis that provides metrics for assessment of care team relations using large-scale health data. These metrics help implementation experts to identify influencers in the network for better design of care intervention programs. The framework is also useful for health services researchers to assess impact of care teams’ relations on patient outcomes. </p> <br> <p> </p>

Striatal oscillatory activity associated with movement, reward, and decision-making is observed in several interacting frequency bands. Rodent striatal local field potential recordings show dopamine- and reward-dependent transitions between a 'spontaneous' state involving beta (15-30 Hz) and low gamma (40-60 Hz) and a 'dopaminergic' state involving theta (4-8 Hz) and high gamma (60-100 Hz) activity. The mechanisms underlying these rhythmic dynamics and their functional consequences are not well understood. In this thesis, I construct a biophysical model of striatal microcircuits that comprehensively describes the generation and interaction of these rhythms as well as their modulation by dopamine and rhythmic inputs, and test its predictions using human electroencephalography (EEG) data. Chapter 1 describes the striatal model and its dopaminergic modulation. Building on previous work suggesting striatal projection neuron (SPN) networks can generate beta oscillations, I construct a model network of striatal fast-spiking interneurons (FSIs) capable of generating delta/theta (2-6 Hz) and gamma rhythms. This FSI network produces low gamma oscillations under low (simulated) dopaminergic tone, and high gamma activity nested within a delta/theta oscillation under high dopaminergic tone. In a combined model under high dopaminergic tone SPN network beta oscillations are interrupted by delta/theta-periodic bursts of gamma-frequency FSI inhibition. This high dopamine-induced periodic inhibition may enable switching between beta-rhythmic SPN cell assemblies representing motor programs, suggesting that dopamine facilitates movement in part by allowing for rapid, periodic changes in motor program execution. Chapter 2 describes the model's response to square-wave periodic cortical inputs. Comparing models with and without FSIs reveals that the FSI network: (i) prevents the SPN network's generation of phase-locked beta oscillations in response to beta's harmonic frequencies, ensuring fidelity of transmission of cortical beta rhythms; and (ii) limits or entrains SPN activity in response to certain gamma frequency inputs. Chapter 3 describes an analysis of phase-amplitude coupling at cortical electrodes in human EEG data during a reward task. The alternating rhythms predicted by the model appear in response to positive feedback. While the origins of these rhythms remain unclear, if they represent striatal signals, they provide a direct link between human behavior and striatal cellular function.