Qualitative Analysis of Social and Sexual Network Characteristics of Black Men
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Adolescent Social Networks and Sexual Practices Wassie Kebede
Social Networks and Sexual Practices ____________________________________________________________________________ Adolescent Social Networks and Sexual Practices Wassie Kebede B.A., Addis Ababa University M.A., Addis Ababa University A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY In Social Work & Social Development © Wassie Kebede, 2009 Addis Ababa University All Rights Reserved. This dissertation may not be reproduced in whole or in part, by photocopying or other means, without the permission of the author Social Networks and Sexual Practices ii ___________________________________________________________________________ Social Networks and Sexual Practices iii ______________________________________________________________________________ Abstract This study examines adolescent social networks and sexual practices (and how they differ among males and females of different ages) among ninth-grade students in two high schools in Addis Ababa, Ethiopia. Social exchange theory and group socialization theory guide the study. Other theories that the study utilizes are the theory of homophily, balance theory, the theory of self-interest, and the theory of early sexual practices. Up to now, there has been no systematic research in Ethiopia or the rest of Africa on the relationship between adolescent social networks and sexual practices. Mixed-methods research guides the study, which consists of two parts. Study A generated data from a 264-item survey of 167 respondents, to which parametric and nonparametric statistics (using a consistent alpha of .05) are applied. Study B used 10 critical cases to generate qualitative data. Critical cases are study participants selected based on their capacity to provide reliable data of interest. UCINET 6.0 was used to draw social network diagrams, and qualitative data were transcribed and subjected to content analysis. -
Dynamic Social Network Analysis: Present Roots and Future Fruits
Dynamic Social Network Analysis: Present Roots and Future Fruits Ms. Nancy K Hayden Project Leader Defense Threat Reduction Agency Advanced Systems and Concepts Office Stephen P. Borgatti, Ronald L. Breiger, Peter Brooks, George B. Davis, David S. Dornisch, Jeffrey Johnson, Mark Mizruchi, Elizabeth Warner July 2009 DEFENSE THREAT REDUCTION AGENCY •ADVANCED SYSTEMS AND CONCEPTS OFFICE REPORT NUMBER ASCO 2009 009 The mission of the Defense Threat Reduction Agency (DTRA) is to safeguard America and its allies from weapons of mass destruction (chemical, biological, radiological, nuclear, and high explosives) by providing capabilities to reduce, eliminate, and counter the threat, and mitigate its effects. The Advanced Systems and Concepts Office (ASCO) supports this mission by providing long-term rolling horizon perspectives to help DTRA leadership identify, plan, and persuasively communicate what is needed in the near term to achieve the longer-term goals inherent in the agency’s mission. ASCO also emphasizes the identification, integration, and further development of leading strategic thinking and analysis on the most intractable problems related to combating weapons of mass destruction. For further information on this project, or on ASCO’s broader research program, please contact: Defense Threat Reduction Agency Advanced Systems and Concepts Office 8725 John J. Kingman Road Ft. Belvoir, VA 22060-6201 [email protected] Or, visit our website: http://www.dtra.mil/asco/ascoweb/index.htm Dynamic Social Network Analysis: Present Roots and Future Fruits Ms. Nancy K. Hayden Project Leader Defense Threat Reduction Agency Advanced Systems and Concepts Office and Stephen P. Borgatti, Ronald L. Breiger, Peter Brooks, George B. Davis, David S. -
Sexual Network Analysis of a Gonorrhoea Outbreak P De, a E Singh, T Wong, W Yacoub, a M Jolly
280 Sex Transm Infect: first published as 10.1136/sti.2003.007187 on 4 August 2004. Downloaded from ORIGINAL ARTICLE Sexual network analysis of a gonorrhoea outbreak P De, A E Singh, T Wong, W Yacoub, A M Jolly ............................................................................................................................... Sex Transm Infect 2004;80:280–285. doi: 10.1136/sti.2003.007187 Objectives: Sexual partnerships can be viewed as networks in order to study disease transmission. We examined the transmission of Neisseria gonorrhoeae in a localised outbreak in Alberta, Canada, using measures of network centrality to determine the association between risk of infection of network members and their position within the sexual network. We also compared risk in smaller disconnected components with a large network centred on a social venue. Methods: During the investigation of the outbreak, epidemiological data were collected on gonorrhoea cases and their sexual contacts from STI surveillance records. In addition to traditional contact tracing information, subjects were interviewed about social venues they attended in the past year where casual sexual partnering may have occurred. Sexual networks were constructed by linking together named See end of article for authors’ affiliations partners. Univariate comparisons of individual network member characteristics and algebraic measures of ....................... network centrality were completed. Results: The sexual networks consisted of 182 individuals, of whom 107 were index cases with laboratory Correspondence to: Prithwish De, Department confirmed gonorrhoea and 75 partners of index cases. People who had significantly higher information of Epidemiology and centrality within each of their local networks were found to have patronised a popular motel bar in the Biostatistics, McGill main town in the region (p = 0.05). -
Examples of Online Social Network Analysis Social Networks
Examples of online social network analysis Social networks • Huge field of research • Data: mostly small samples, surveys • Multiplexity Issue of data mining • Longitudinal data McPherson et al, Annu. Rev. Sociol. (2001) New technologies • Email networks • Cellphone call networks • Real-world interactions • Online networks/ social web NEW (large-scale) DATASETS, longitudinal data New laboratories • Social network properties – homophily – selection vs influence • Triadic closure, preferential attachment • Social balance • Dunbar number • Experiments at large scale... 4 Another social science lab: crowdsourcing, e.g. Amazon Mechanical Turk Text http://experimentalturk.wordpress.com/ New laboratories Caveats: • online links can differ from real social links • population sampling biases? • “big” data does not automatically mean “good” data 7 The social web • social networking sites • blogs + comments + aggregators • community-edited news sites, participatory journalism • content-sharing sites • discussion forums, newsgroups • wikis, Wikipedia • services that allow sharing of bookmarks/favorites • ...and mashups of the above services An example: Dunbar number on twitter Fraction of reciprocated connections as a function of in- degree Gonçalves et al, PLoS One 6, e22656 (2011) Sharing and annotating Examples: • Flickr: sharing of photos • Last.fm: music • aNobii: books • Del.icio.us: social bookmarking • Bibsonomy: publications and bookmarks • … •“Social” networks •“specialized” content-sharing sites •Users expose profiles (content) and links -
Evolving Networks and Social Network Analysis Methods And
DOI: 10.5772/intechopen.79041 ProvisionalChapter chapter 7 Evolving Networks andand SocialSocial NetworkNetwork AnalysisAnalysis Methods and Techniques Mário Cordeiro, Rui P. Sarmento,Sarmento, PavelPavel BrazdilBrazdil andand João Gama Additional information isis available atat thethe endend ofof thethe chapterchapter http://dx.doi.org/10.5772/intechopen.79041 Abstract Evolving networks by definition are networks that change as a function of time. They are a natural extension of network science since almost all real-world networks evolve over time, either by adding or by removing nodes or links over time: elementary actor-level network measures like network centrality change as a function of time, popularity and influence of individuals grow or fade depending on processes, and events occur in net- works during time intervals. Other problems such as network-level statistics computation, link prediction, community detection, and visualization gain additional research impor- tance when applied to dynamic online social networks (OSNs). Due to their temporal dimension, rapid growth of users, velocity of changes in networks, and amount of data that these OSNs generate, effective and efficient methods and techniques for small static networks are now required to scale and deal with the temporal dimension in case of streaming settings. This chapter reviews the state of the art in selected aspects of evolving social networks presenting open research challenges related to OSNs. The challenges suggest that significant further research is required in evolving social networks, i.e., existent methods, techniques, and algorithms must be rethought and designed toward incremental and dynamic versions that allow the efficient analysis of evolving networks. Keywords: evolving networks, social network analysis 1. -
Basics of Social Network Analysis Distribute Or
1 Basics of Social Network Analysis distribute or post, copy, not Do Copyright ©2017 by SAGE Publications, Inc. This work may not be reproduced or distributed in any form or by any means without express written permission of the publisher. Chapter 1 Basics of Social Network Analysis 3 Learning Objectives zz Describe basic concepts in social network analysis (SNA) such as nodes, actors, and ties or relations zz Identify different types of social networks, such as directed or undirected, binary or valued, and bipartite or one-mode zz Assess research designs in social network research, and distinguish sampling units, relational forms and contents, and levels of analysis zz Identify network actors at different levels of analysis (e.g., individuals or aggregate units) when reading social network literature zz Describe bipartite networks, know when to use them, and what their advan- tages are zz Explain the three theoretical assumptions that undergird social networkdistribute studies zz Discuss problems of causality in social network analysis, and suggest methods to establish causality in network studies or 1.1 Introduction The term “social network” entered everyday language with the advent of the Internet. As a result, most people will connect the term with the Internet and social media platforms, but it has in fact a much broaderpost, application, as we will see shortly. Still, pictures like Figure 1.1 are what most people will think of when they hear the word “social network”: thousands of points connected to each other. In this particular case, the points represent political blogs in the United States (grey ones are Republican, and dark grey ones are Democrat), the ties indicating hyperlinks between them. -
Religion Networks and Hiv/Aids in Rural Malawi
RELIGION NETWORKS AND HIV/AIDS IN RURAL MALAWI DISSERTATION Presented in Partial Fulfillment of the Requirements for The Degree of Doctor of Philosophy in the Graduate School of Ohio State University By jimi adams * * * * * Ohio State University 2007 Dissertation Committee: Approved by Professor Kazimierz M. Slomczynski, Advisor Professor James W. Moody, Outside Member _______________________ Professor Korie Edwards Advisor Sociology Graduate Program Professor Steven H. Lopez Copyright by jimi adams 2007 ABSTRACT Sub-Saharan Africa’s residents represent approximately two-thirds of the nearly 40 million global HIV/AIDS cases, while comprising only about one-tenth of the world’s population. In the rural settings where most inhabitants of SSA live, religious organizations are the only formal organizations present, and virtually all residents of SSA participate in a religious organization. Many have theorized a relationship between religion and HIV/AIDS, suggesting alternately its helpful and harmful potential in this crisis. The existing research conceptualizes religion, HIV risk and the connection between them by studying individuals, organizations, or aggregations of individuals and organizations. In this dissertation, I demonstrate the adjustments a network perspective contributes to researchers’ ability to understand religious organizational responses to this epidemic, the nature of HIV-risk and, perhaps most importantly, how these are linked. The resulting conceptualization suggests some of the first mechanisms that demonstrate how -
The Effect of Social Media Use on Physical Isolation in Individuals with Borderline Personality Disorder
Walden University ScholarWorks Walden Dissertations and Doctoral Studies Walden Dissertations and Doctoral Studies Collection 2021 The Effect of Social Media use on Physical Isolation in Individuals with Borderline Personality Disorder Davena Limitless Longshore Walden University Follow this and additional works at: https://scholarworks.waldenu.edu/dissertations Part of the Clinical Psychology Commons, Computer Sciences Commons, and the Quantitative, Qualitative, Comparative, and Historical Methodologies Commons This Dissertation is brought to you for free and open access by the Walden Dissertations and Doctoral Studies Collection at ScholarWorks. It has been accepted for inclusion in Walden Dissertations and Doctoral Studies by an authorized administrator of ScholarWorks. For more information, please contact [email protected]. Walden University College of Social and Behavioral Sciences This is to certify that the doctoral dissertation by Davena L. Longshore has been found to be complete and satisfactory in all respects, and that any and all revisions required by the review committee have been made. Review Committee Dr. Georita Frierson, Committee Chairperson, Psychology Faculty Dr. Alethea Baker, Committee Member, Psychology Faculty Dr. Michael Johnson, University Reviewer, Psychology Faculty Chief Academic Officer and Provost Sue Subocz, Ph.D. Walden University 2021 Abstract The Effect of Social Media use on Physical Isolation in Individuals with Borderline Personality Disorder. by Davena L. Longshore MS, Walden University, 2017 MIS, University of Phoenix, 2008 BA, Florida Atlantic University, 2004 Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Clinical Psychology Walden University August 2021 Abstract Individuals with borderline personality disorder (BPD) experience extreme interpersonal conflict, crippling their ability to sustain successful relationships. -
Chains of Affection: the Structure of Adolescent Romantic and Sexual Networks
Chains of Affection: The Structure of Adolescent Romantic and Sexual Networks Peter S. Bearman* Institute for Social and Economic Research and Policy Columbia University James Moody Department of Sociology Ohio State University Katherine Stovel Department of Sociology University of Washington 9960 words 10 figures 5 tables Data for this paper are drawn from the National Longitudinal Study of Adolescent Health (Add Health), a program project designed by J. Richard Udry and Peter Bearman, and funded by a grant HD31921 from the National Institute of Child Health and Human Development to the Carolina Population Center, University of North Carolina at Chapel Hill, with cooperative funding participation by the following agencies: The National Cancer Institute; The National Institute of Alcohol Abuse and Alcoholism; the National Institute on Deafness and other Communication Disorders; the National Institute on Drug Abuse; the National Institute of General Medical Sciences; the National Institute of Mental health; the Office of AIDS Research, NIH; the Office of Director, NIH; The National Center for Health Statistics, Centers for Disease Control and Prevention, HHS; Office of Minority Health, Centers for Disease Control and prevention, HHS, Office of the Assistant Secretary for Planning and Evaluation, HHS; and the National Science Foundation. The authors thank Douglas White, Martina Morris, Mark Hancock, and J. Richard Udry for helpful comments on previous drafts of this paper. *Corresponding author. Institute for Social and Economic Research and Policy. 814 SIPA Building, Columbia University, New York NY 10027. Email: [email protected] 1 Abstract: Recognizing the actual structure of sexual networks is critical for modeling the potential for disease transmission, if disease is spread via sexual contact. -
Likelihood-Based Inference for Stochastic Models of Sexual Network Formation
Likelihood-Based Inference for Stochastic Models of Sexual Network Formation Mark S. Handcock Center for Statistics and the Social Sciences Department of Statistics University of Washington, Seattle, WA James Holland Jones1 Center for Studies in Demography and Ecology Center for Statistics and the Social Sciences Center for AIDS and Sexually Transmitted Diseases University of Washington, Seattle, WA 29 January 2003 Working Paper #29 Center for Statistics and the Social Sciences University of Washington Box 354322 Seattle, WA 98195-4322, USA 1Corresponding Author: Center for Statistics and the Social Sciences, Box 354320, Seattle, WA 98195- 4320, email: [email protected], Phone: 206-221-6874, Fax: 206-221-6873 Abstract Sexually-Transmitted Diseases (STDs) constitute a major public health concern. Mathematical models for the transmission dynamics of STDs indicate that heterogeneity in sexual activity level allow them to persist even when the typical behavior of the population would not support endemicity. This insight focuses attention on the distribution of sexual activity level in a pop- ulation. In this paper, we develop several stochastic process models for the formation of sexual partnership networks. Using likelihood-based model selection procedures, we assess the fit of the different models to three large distributions of sexual partner counts: (1) Rakai, Uganda, (2) Sweden, and (3) the USA. Five of the six single-sex networks were fit best by the negative binomial model. The American women’s network was best fit by a power-law model, the Yule. For most networks, several competing models fit approximately equally well. These results sug- gest three conclusions: (1) no single unitary process clearly underlies the formation of these sexual networks, (2) behavioral heterogeneity plays an essential role in network structure, (3) substantial model uncertainty exists for sexual network degree distributions. -
Applying Social Network Analysis to Identify Project Critical Success Factors
sustainability Article Applying Social Network Analysis to Identify Project Critical Success Factors Marco Nunes 1,* and António Abreu 2,* 1 Industrial Engineering Department, University of Beira Interior, 6201-001 Covilhã, Portugal 2 Mechanical Engineering Department, Polytechnic Institute of Lisbon and CTS Uninova, 1959-007 Lisbon, Portugal * Correspondence: [email protected] or [email protected] (M.N.); [email protected] (A.A.) Received: 13 January 2020; Accepted: 14 February 2020; Published: 18 February 2020 Abstract: A key challenge in project management is to understand to which extent the dynamic interactions between the different project people—through formal and informal networks of collaboration that temporarily emerge across a project´s lifecycle—throughout all the phases of a project lifecycle, influence a project’s outcome. This challenge has been a growing concern to organizations that deliver projects, due their huge impact in economic, environmental, and social sustainability. In this work, a heuristic two-part model, supported with three scientific fields—project management, risk management, and social network analysis—is proposed, to uncover and measure the extent to which the dynamic interactions of project people—as they work through networks of collaboration—across all the phases of a project lifecycle, influence a project‘s outcome, by first identifying critical success factors regarding five general project collaboration types ((1) communication and insight, (2) internal and cross collaboration, (3) know-how and power sharing, (4) clustering, and (5) teamwork efficiency) by analyzing delivered projects, and second, using those identified critical success factors to provide guidance in upcoming projects regarding the five project collaboration types. -
Social Networks of Men Who Have Sex with Men: a Study of Recruitment Chains Using Respondent Driven Sampling in Salvador, Bahia State, Brazil
S170 ARTIGO ARTICLE Social networks of men who have sex with men: a study of recruitment chains using Respondent Driven Sampling in Salvador, Bahia State, Brazil Redes sociais de homens que fazem sexo com homens: estudo das cadeias de recrutamento com Respondent Driven Sampling em Salvador, Bahia, Brasil Las redes sociales de hombres que mantienen sexo con hombres: estudio de muestreo en Sandra Mara Silva Brignol 1 cadena con Respondent Driven Sampling Inês Dourado 1 Leila Denise Amorim 2 en Salvador, Bahía, Brasil José Garcia Vivas Miranda 3 Lígia R. F. S. Kerr 4 Abstract Resumo 1 Instituto de Saúde Coletiva, Social and sexual contact networks between men As redes sociais e de contato sexual entre homens Universidade Federal da Bahia, Salvador, Brasil. who have sex with men (MSM) play an impor- que fazem sexo com homens (HSH) têm um pa- 2 Instituto de Matemática, tant role in understanding the transmission of pel importante na compreensão da ocorrência de Universidade Federal da HIV and other sexually transmitted infections doenças sexualmente transmissíveis (DST) e HIV, Bahia, Salvador, Brasil. 3 Instituto de Física, (STIs). In Salvador (Bahia State, Brazil), one of devido ao potencial de circulação de agentes in- Universidade Federal da the cities in the survey Behavior, Attitudes, Prac- fecciosos nestas estruturas. Dados da Cidade de Bahia, Salvador, Brasil. tices, and Prevalence of HIV and Syphilis among Salvador, Bahia, Brasil, que integraram a pesquisa 4 Faculdade de Medicina, Universidade Federal da Men Who Have Sex with Men in 10 Brazilian Comportamento, Atitudes, Práticas e Prevalência Ceará, Fortaleza, Brasil. Cities, data were collected in 2008/2009 from a de HIV e Sífilis entre Homens que Fazem Sexo sample of 383 MSM using Respondent Driven com Homens em 10 Cidades Brasileiras foram Correspondence S.