Browsing by Subject "Social network analysis"

Now showing 1 - 6 of 6
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    Academic and Social Acclimation of Medical Students Following a Prematriculation Program
    (2016) Skildum, Andrew; Kosobuski, Anna W; Prunuske, Amy; Whitney, Abigail
    Transitioning to medical school is challenging. To help ease this transition, medical schools across the country have implemented summer online courses, supplemental instruction, and pre-matriculation programs. Pre-matriculation programs offer the unique opportunity to acclimate students to the academic rigor and culture of medical school. The University of Minnesota Medical School Duluth Campus offers a summer pre-matriculation program to students from disadvantaged backgrounds and underrepresented populations in medicine. The program coincides with the school’s mission to train students who are committed to practicing family medicine that serves rural Minnesota and American Indian communities. Through this program, students gain academic knowledge, study-skills, and a support-network of faculty and peers. Evaluation of scores on a microbiology concept inventory exam of participants before and after the pre-matriculation program compared to their peers showed academic gains of the participants. A focus group with pre-matriculation participants was conducted over three years to help evaluate the strengths and weaknesses of the program. Interviews were conducted with non-participants, students who were invited to participate in the program but chose not to attend, in order to gain insight into strategies to improve participation in the program and observe differences between participants and non-participants. Focus groups were also conducted with peer mentors, participants from previous years who assisted the students during the program. Repeating first-year students were invited to attend and reported unique benefits of the program to returning students in a focus group. To assess the program’s impact on social and studying networks, social network analysis was conducted on three years of medical students to evaluate the impacts and longevity of connections made during the pre-matriculation program. The social network analysis also identified the unique studying and social networks of medical students. Evaluating the social networks, academic gains, and participant perception of the program will help the University of Minnesota Medical School Duluth Campus improve the pre-matriculation program and further support underrepresented students.
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    Analyzing information flow in social networks for knowledge discovery
    (2013-02) Pathak, Nishith
    In the last few years the online world has seen a surge in users’ social behavior. No longer is the image of a lone user surfing the web relevant anymore and with social sites such as Facebook, Twitter, etc. online users can now actively interact with other users. It is now quite common for web businesses to offer support for friends lists, forums, private message systems, community maintenance tools etc. As as result, not only are users finding more social satisfication online, but the businesses themselves are now able to interact with and monitor the communities around them. Consequently, large amounts of data are being collected from such “social systems”, which capture users’ participation in the community. The data can include user-user interactions as well as their activities with time stamps. The data is also unique in that it captures complex social phenomenon in a much more comprehensive manner and at a much more finer granularity, than any other traditional source of communication data. This presents rich opportunities for the development of knowledge discovery algorithms which will find immense value in revealing trends, latent structures or interesting behaviors in these social systems. In any social system, communication exposes people to information, opinions as well as behavior of other users. According to a well studied phenomenon in social science, summarized in the theory of contagion, users in such networks tend to develop beliefs, attitudes and assumptions that are similar to those of others around them. By “word-of-mouth” rumors, ideas, opinions, information, etc. can propagate to different regions in the network. The research presented in this thesis explores the analysis of such information flow in social networks from a variety of perspectives, including the network topology, actors’ interests, actors’ cognition and actors’ influence. It is shown that the proposed analyses techniques can discover valuable knowledge regarding community structure, user interests and sentiments, as well as prominent users in the community. Such knowledge is of immense value to online business owners, as it allows them to monitor and identify factors for improving the overall experience of their users.
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    Impact of co-authorship strategies on research productivity: a social-network analysis of publications in Russian cardiology.
    (2011-05) Kuzhabekova, Aliya
    This study explores how the choice of a co-authorship strategy determines individual research productivity measured in terms of quantity of publications. The exploration is conducted in the specific context of Russian cardiologic research.The concept of social capital is used to explain the relationship between co-authorship and increased research productivity. The methodology for theoretical classification and empirical determination of co-authorship strategies is based on theoretical and methodological foundations borrowed from social network analysis. Two competing theories explaining the relationship between social network structure and social capital by Coleman (1988) and Burt (1992) are used to classify and to determine empirically co-authorship strategies. The study is conducted in three phases. First, social network analysis is used to determine the co-authorship strategy of each researcher in the study. Second, analysis of variance is applied to determine the effect of co-authorship strategies on individual research productivity. Third, sensitivity analysis is conducted to determine whether the results hold under different assumptions. The results indicate that co-authorship strategies have differential effects on research productivity and that the bridging strategy, in which a researcher serves as a broker between other researchers, is the most productive in Russian cardiologic research. This finding is consistent with the results of a prior study on the effect of co-authorship strategies on individual research productivity in the US research in higher education (Rumsey-Wairepo, 2006). The study supports Burt's (1992) theory of structural holes in explaining how social network structure creates social capital.
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    Price Discrimination in Large Social Networks
    (2021-05) Huang, Jiali
    Recent trends point to increasing use of social network information by firms and public agencies for personalized policies. However, the cost of implementation can be high and the use of personal information can reduce satisfaction. The value of such policies depends upon network structures, and may be insignificant for certain classes of large networks. Thus, firms and public agencies may need to be more careful about the design of mechanisms within social networks. In this thesis, we focus on a particular application of mechanism design problems with social network effects, i.e., the pricing problem of a single firm selling a product to consumers in social networks, and study the value of price discrimination in large social networks. Recent trends in industry suggest that increasingly firms are using information about social network to offer personalized prices to individuals based upon their positions in the social network. In the presence of positive network externalities, firms aim to increase their profits by offering discounts to influential individuals that can stimulate consumption by other individuals at a higher price. However, the lack of transparency in discriminative pricing may reduce consumer satisfaction and create mistrust. Recent research has focused on the computation of optimal prices in deterministic networks under positive externalities. We would like to answer the question: how valuable is such discriminative pricing? We find, surprisingly, that the value of such pricing policies (increase in profits due to price discrimination) in very large random networks are often not significant. Particularly, for Erd\"{o}s-Renyi random networks, we provide the exact rates at which this value decays in the size of the networks for different ranges of network densities. Our results show that there is a non-negligible value of price discrimination for a small class of moderate-sized Erd\"{o}s-Renyi random networks. We also present a framework to obtain bounds on the value of price discrimination for random networks with general degree distributions and apply the framework to obtain bounds on the value of price discrimination in power-law networks. Our numerical experiments demonstrate our results and suggest that our results are robust to changes in the model of network externalities.
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    The role of information flow in climate change policy formation in New Zealand: a social analysis.
    (2012-08) Vaughter, Philip Claude-Dziuk
    Climate change threatens all nations of the world with risk of adverse environmental consequences. Science has linked the mechanisms of climate change to the emission of greenhouse gases produced by human industry. Yet despite this, most societies around the globe lack the incentive to implement national policy to mitigate climate change for fear of short-term economic loss. New Zealand is the first nation outside of the European Union to create an Emissions Trading Scheme (ETS) to decrease the amount of greenhouse gases emitted into the atmosphere from domestic greenhouse gas emissions, the majority of which come from agricultural production. In this study, I examine the discourse about climate change in New Zealand's media and examine though survey data how different sectors of the economy responded to impending carbon legislation. To do this I model communication networks that operated in New Zealand to disseminate climate science from the IPCC and other research organizations. I also examine the action network that formed an advocacy coalition around passage of the ETS. This research is an extensive study of how climate change was operationalized within New Zealand and how a policy instrument was drafted and passed in order to address climate change.
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    Structuring the Use of Social Network Analysis in Program Evaluation
    (2022-12) Zhang, Lixin
    Social network analysis (SNA) is increasingly viewed as a contributing methodology to program evaluation to examine the complexities of social programs and interrelationships within the program networks. Despite the growing literature on the topic, more knowledge is needed to understand how, when, and under what conditions social network analysis can add value to evaluation work. The study's overall purpose was to explore the ways of applying SNA to support program evaluation. Using a sequential mixed method social network analysis (MMSNA) approach, this study first developed the SNA-Evaluation framework based on existing literature. Guided by the SNA-Evaluation framework, this study applied the SNA method to support the evaluation of the Community-Based Opioid Prevention and Education (C.O.P.E.) program. Data for the study were collected through a review of 30 archival documents, a C.O.P.E. Partnership Network survey to 46 partner organizations, and semi-structured interviews of 8 program stakeholders. The results suggested that evaluators can adopt the SNA method to support their evaluation practices depending on the types of evaluation, such as needs assessment, process evaluation, and outcome evaluation. The study also observed that the use of SNA in the field of evaluation, particularly for responding to complex social programs, can sharpen program theories, strengthen evaluation methods by enabling the assessment of complex adaptive system variables, and maximize evaluation instrumental and conceptual use. The study contributes to the body of research on evaluation methods by exploring an alternative methodology that can add value to evaluation practice. The study benefits the knowledge base in program evaluation by providing the SNA-Evaluation framework and screening tool to help evaluators determine more appropriate steps when applying the SNA method to support their evaluation work. This study has implications for evaluators (1) who have an interest in improving their SNA use in program evaluation, (2) who hope to explore more about the theories behind the use of the SNA method in program evaluation, and (3) who support the evaluation of complex social programs.