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Performing social network analysis (SNA) requires a set of powerful techniques to analyze structural information contained in interactions between social entities. Many SNA technologies and methodologies have been developed and have successfully provided significant insights for small-scale interactions. However, these techniques are not suitable for analyzing large social networks, which are very popular and important in various fields and have special structural properties that cannot be obtained from small networks or their analyses. There are a number of issues that need to be further studied in the design of current SNA techniques. A number of key issues can be embodied in three fundamental and critical challenges: long processing time, large computational resource requirements, and network dynamism. In order to address these challenges, we discuss an anytime-anywhere methodology based on a parallel/distributed computational framework to effectively and efficiently analyze large and dynamic social networks. In our methodology, large social networks are decomposed into intra-related smaller parts. A coarse-level of network analysis is built based on comprehensively analyzing each part. The partial analysis results are incrementally refined over time. Also, during the analyses process, network dynamic changes are effectively and efficiently adapted based on the obtained results. In order to evaluate and validate our methodology, we implement our methodology for a set of SNA metrics which are significant for SNA applications and cover a wide range of difficulties. Through rigorous theoretical and experimental analyses, we demonstrate that our anytime-anywhere methodology is / Ph. D.

This dissertation consists of three essays in Health Economics relating to the recent challenges in the U.S. The first essay studies the impact of retirement on subsequent health and investigates the mediation effect of social network in the relationship between retirement and health. Findings reveal that retirement adversely impacts physical and mental health outcomes and a considerable portion of these effects are explained by social network changes post-retirement. In particular, shrinkage in the size of social network post-retirement deteriorates physical health and increases depression in retirees. In the second essay, we assess the differential effect of social distancing on the daily growth rate of COVID-19 infections in the US counties by considering the spatial pattern of COVID-19 spread. We also conduct a comparative analysis of the effect on urban versus rural counties, as well as low versus high socially vulnerable counties. Our analysis illustrates that a high level of social distancing compliance is needed in urban counties and in socially vulnerable areas to achieve the largest impact at curve flattening, whereas moderate-compliance is enough in reaching the peak marginal impact in rural regions and counties with low social vulnerability. In the third essay, by combining multiple data sources, we investigate how racial disparities in access to healthcare contribute to the disparity in COVID-19 infections and mortality in black versus white sub-groups. The multilevel analysis demonstrates that a higher probability of having health insurance significantly reduces disparity in COVID-19 mortality in black sub-group while it has no impact on the disparity in whites. / Doctor of Philosophy / This dissertation uses various quantitative methods to investigate policy-relevant questions regarding the recent challenges in the U.S. economy. In the first chapter, we explore how the physical and mental health of individuals changes by retirement. The results show that retirement decreases physical health while increases depression and anxiety. We also analyze how social network changes after retirement might cause changes in the health of retirees. We find that retirees may experience worse physical and mental health than non-retirees due to losing some of their relationships after retirement. In particular, the loss of contacts increases depression and deteriorates general health. In the second chapter, we investigate how compliance with social distancing within a typical county and its neighbor counties can reduce the spread of COVID-19. We examine this question for urban versus rural counties in the US and socially vulnerable versus socially not vulnerable counties. We find a high compliance level of social distancing is needed in urban counties and in socially vulnerable areas to reach the highest impact at slowing down the COVID-19 virus spread. In the third chapter, we examine whether healthcare access inequalities (e.g., having health insurance) increase the risk of COVID-19 infections and mortality for black communities. Our results show that having health insurance decreases COVID-19 mortality in communities of color but not whites.

I analyze the relationship between insider trading outcomes and insiders' information environment within a network. While most existing studies rely on one dimension of commonality (e.g., personal ties, professional ties, geographic proximity) to construct the social network, I document the formation of the institutional investor groups (cliques) that exogenously connect firm-level insiders within the social network. Using difference-in-differences designs examining changes in clique size, I provide empirical evidence on the information dissemination channels within a network in which its members are quasi-randomly selected. Insider transactions in larger cliques exhibit lower abnormal trading profits, higher level of trading frequency, and larger amount of trade size, suggesting information dissemination is increasing in clique size. Then, I provide empirical evidence that the association between the value of information and the information dissemination rate is monotonic, consistent with prior theoretical studies. / Doctor of Philosophy / People communicate and are influenced by other people when they reside in a social network. I analyze how corporate insiders' trading outcomes are influenced by their information environment within a network. Most current research rely on one specific type of connection (e.g., personal relationships, professional relationships, geographic proximity) to build the social network, I provide evidence that firm-level insiders are involuntarily connected by the institutional investor social network (cliques). Using archival study approach, I document that insider transactions in larger cliques exhibit lower abnormal trading profits, higher level of trading frequency, and larger amount of trade size, suggesting information dissemination is increasing in clique size. Then, I provide empirical evidence that the association between the value of information and the information dissemination rate is linear, consistent with prior theoretical studies.

This thesis examines development as a catalyst for the decision to migrate. Specifically, the two complementary theories of relative deprivation and social networks are examined to explore possible associations between level of household development and migrants' designation of savings or remittances towards development-related purposes and whether remittances are positively affected by migrants' participation in a hometown association (HTA). The study relied on data from the Mexican Migration Project (MMP), using the historical Mexican sending state of Jalisco. The MMP, using an ethnosurvey method, gathers data on individual migrant experiences, including border-crossing methods, jobs held, and participation in migrant hometown associations, amenities found in individual households, and available services in communities. No support was found for the first hypothesis, which predicted that relative deprivation was a catalyst of migration. Support was found for the second hypothesis, that migrant participation in HTAs, specifically in social clubs, positively influenced designation of savings or remittances for development-related purposes. This same support was not the case for migrant involvement in sport clubs. This thesis contributes to social network theory, pinpointing the positive effect that migrant participation in hometown associations has on designating money towards development. / Master of Arts

Social Network Sites allow individuals to construct a public or semi-public profile within a bounded system, articulate a list of other users with whom they share a connection, and view and traverse their list of connections and those made by others within a system. Such sites are generally centered around a particular activity, such as maintaining social relationships or uploading user created content. Increasingly, niche domains such as education, healthcare and software development have been exploring the creation of social network sites centered around the activities of the domain. This has led to an increasing focus on the processes involved in designing and evaluating these sites. We argue that social network sites require a specialized focus in their design and evaluation on the social utility of the features on the site. We have created two social network sites for niche communities: Colloki, a conversation platform designed for members of local communities; and CATspace, a social repository of Computer Science assignments, designed for use by CS instructors and students. In this thesis, we describe the motivation, design and implementation of these two sites. We provide a formative evaluation of these two sites, wherein we evaluate the usability, and study the perceived social affordances of individual features across the two site. Finally, we discuss future work towards building a framework for evaluating the social utility of Social Network Sites at a formative stage. / Master of Science

Yes / Social media have become an important interaction channel between the government and citizens in the era of the digital community. The adoption of social media in local government services offers a new channel to encourage citizen engagement in the public policy decision-making process. Moreover, communication with citizens through social media exposes large opportunities for the local government to analyse and appreciate the relationships among social media participants in the digital community to enhance public services. The purpose of this study is to understand the local government’s social media network and identify the social role in the local government’s social media network structure. Thus, this study adopted the social network analysis (SNA) approach on the Twitter data of a local government’s official account in the UK as a case study. The study revealed that the internal local government stakeholders play an important social role in the local government’s social media network. The implication of the study was discussed.