The U.S. has undergone macroeconomic changes over the latter course of the twentieth century. As a result, migration patterns have shifted toward the fast-growing southern and western portions of the nation. My research measures the impact of deindustrialization and educational selection on out-migration from the metropolitan Rust Belt for 1980, 1990, and 2000. Analysis on destination selection using multinomial regression analysis is then conducted to determine whether education trumps social capital for long-distance migration. Findings indicate that more severely deindustrializing metropolitan areas have greater out-migration in 1980 and 1990 but less so for 2000, with positive educational selection for each year. Multinomial results indicate that education does not attenuate social capital for interregional migration destination. The rise of the service economy may indicate the increasing importance of social capital for individuals leaving the Rust Belt for other regions.

No description available.

No description available.

No description available.

This study investigated the social networks developed by language learners and their relationship with perceived changes in the learners' fluency in the context of an intensive English as a second language (ESL) program. Using data from the Study Abroad Social Interaction Questionnaire (SASIQ) to determine SN development and native speaker ratings to determine perceived fluency, a simple linear regression to test the relationship between social network variables and fluency gain, as well as a hierarchical regression measuring (a) the combined effect of variables previously found to be significant in fluency gain, and (b) the additional joint effect of the remaining social network variables. We found that participants were successful in developing complex social networks, and that their oral fluency did increase significantly in connection with their social networks. Density (the average number of people listed in a social group) was the most important factor when only social network variables were considered. In the hierarchical regression, initial proficiency level and the percentage of native English speakers in the network were the most significant of the established variables in the first step, and overall size and density were the most important of the added social network variables in the second step.

The ingrained economic, political, and cultural structures in society create difficulties for people to change consumption habits because they have existed in society for a long time where individuals’ social networks affect consumption. The purpose of this research has been to highlight and analyze the effect of the connection between social network and consumption and to reflect on how one's social network affects consumption habits. A quantitative survey using the 2018 Living Costs and Food Survey dataset with 5000 respondents was conducted for this reason. Social cost was used as a measure to highlight the effect it has on consumption. The result highlighted that material products acted as symbolic capital that the respondents consumed to strengthen their social ties that existed within their social networks.

No description available.

Analysis of large network datasets has become increasingly important. Algorithms have been designed to find many kinds of structure, with numerous applications across the social and biological sciences. However, a tradeoff is always present between accuracy and scalability; otherwise promising techniques can be computationally infeasible when applied to networks with huge numbers of nodes and edges. One way of extending the reach of network analysis is to sparsify the graph by retaining only a subset of its edges. The reduced network could prove much more tractable. For this thesis, I propose a new sparsification algorithm that preserves the properties of a random walk on the network. Specifically, the algorithm finds a subset of edges that best preserves the stationary distribution of a random walk by minimizing the Kullback-Leibler divergence between a walk on the original and sparsified graphs. A highly efficient greedy search strategy is developed to optimize this objective. Experimental results are presented that test the performance of the algorithm on the influence maximization task. These results demonstrate that sparsification allows near-optimal solutions to be found in a small fraction of the runtime that would required using the full network. Two cases are shown where sparsification allows an influence maximization algorithm to be applied to a dataset that previous work had considered intractable.

The primary purpose of this study was to identify dimensions of weak tie relationships including characteristics (e.g., distinctive qualities, traits, or properties), functions (e.g., outcomes, purposes, or meanings derived from the interaction) and determinants of engagement to gain insight into the weak tie exchange process and develop frameworks that can be used to operationalize the concept. Data were collected through stories provided by participants during face-to-face interviews. Respondents recounted a situation when someone they did not know well and to whom they did not feel particularly close provided them with assistance. Over 70 stories were collected from 50 adults aged 65 and older who were active in their community. Stories collected were analyzed using an inductive approach that was supported by the concepts of interpersonal tie strength, loose connections, social exchange theory, and social support. Findings suggest that weak tie relationships occur in a variety of community settings and in response to a variety of daily challenges. The exchanges occur more frequently with acquaintances than strangers and the initiator of the exchange is generally the person offering support. The types of support offered are broad-based and include instrumental, emotional, and informational support. Weak tie exchanges range from one-time brief interactions to intermittent exchanges over extended periods, depending on the circumstances. Findings also suggest that weak ties have a specific task or purpose, encourage awareness about the value and purpose of social interactions, and influence participants' future social interactions. Six factors were identified as determinants of engagement in weak ties: situational factors, personal characteristics, judgments of responsibility, attitudes about helping behaviors, personal network type, and exchange history. The findings from this study provide a foundation for further conceptualization of weak ties and a framework on which to develop instruments to measure tie strength and the potential for engaging in weak tie exchanges. / Ph. D.

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.