Social Networks Sociology 290, Sem 1
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Creating & Connecting: Research and Guidelines on Online Social
CREATING & CONNECTING//Research and Guidelines on Online Social — and Educational — Networking NATIONAL SCHOOL BOARDS ASSOCIATION CONTENTS Creating & Connecting//The Positives . Page 1 Online social networking Creating & Connecting//The Gaps . Page 4 is now so deeply embedded in the lifestyles of tweens and teens that Creating & Connecting//Expectations it rivals television for their atten- and Interests . Page 7 tion, according to a new study Striking a Balance//Guidance and Recommendations from Grunwald Associates LLC for School Board Members . Page 8 conducted in cooperation with the National School Boards Association. Nine- to 17-year-olds report spending almost as much time About the Study using social networking services This study was made possible with generous support and Web sites as they spend from Microsoft, News Corporation and Verizon. watching television. Among teens, The study was comprised of three surveys: an that amounts to about 9 hours a online survey of 1,277 nine- to 17-year-old students, an online survey of 1,039 parents and telephone inter- week on social networking activi- views with 250 school district leaders who make deci- ties, compared to about 10 hours sions on Internet policy. Grunwald Associates LLC, an a week watching TV. independent research and consulting firm that has conducted highly respected surveys on educator and Students are hardly passive family technology use since 1995, formulated and couch potatoes online. Beyond directed the study. Hypothesis Group managed the basic communications, many stu- field research. Tom de Boor and Li Kramer Halpern of dents engage in highly creative Grunwald Associates LLC provided guidance through- out the study and led the 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. -
Tentative Syllabus
University of Wisconsin, Department of Sociology Sociology 375: Introduction to Mathematical Sociology Fall 2014 Prof. James Montgomery [email protected] 2436 Social Science Office hours: Friday 9:30-11:30 AM or by appointment Overview. Mathematical sociologists use mathematics to represent and analyze sociological concepts and theories. In this course, we explore mathematical models of social structure, focusing especially on social network analysis and related methods. A second course in mathematical sociology, Soc 376, which is taught in the spring, focuses on mathematical models of social process, addressing the use of Markov chains and dynamical systems in sociology. Prerequisites. There is no particular mathematics prerequisite. However, past experience suggests that students with weak backgrounds in math often find the course quite difficult. We will make extensive use of matrix algebra (as well as the matrix-algebra software package Matlab), though the course is intended to be self-contained for motivated students who have not already studied this topic. We will also learn and employ some elementary concepts from set theory and graph theory. Students who have taken Math 240 (Discrete Mathematics) and Math 340 (Matrix Algebra) or equivalents will already know the relevant mathematics. Students who have previously used mathematical software and/or have some background in computer programming may have an advantage. There is no sociology prerequisite, so the course is well- suited for students with other (quantitative) majors. Evaluation. Grades will be based on two exams (a midterm and a final), as well as problem sets. The midterm exam will be held in class on Thursday, October 23. -
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. -
Opportunities and Challenges for Standardization in Mobile Social Networks
Opportunities and Challenges for Standardization in Mobile Social Networks Laurent-Walter Goix, Telecom Italia [email protected] Bryan Sullivan, AT&T [email protected] Abstract This paper describes the opportunities and challenges related to the standardization of interoperable “Mobile Social Networks”. Challenges addressed include the effect of social networks on resource usage, the need for social network federation, and the needs for a standards context. The concept of Mobile Federated Social Networks as defined in the OMA SNEW specification is introduced as an approach to some of these challenges. Further specific needs and opportunities in standards and developer support for mobile social apps are described, including potentially further work in support of regulatory requirements. Finally, we conclude that a common standard is needed for making mobile social networks interoperable, while addressing privacy concerns from users & institutions as well as the differentiations of service providers. 1 INTRODUCTION Online Social Networks (OSN) are dominated by Walled Gardens that have attracted users by offering new paradigms of communication / content exchange that better fit their modern lifestyle. Issues are emerging related to data ownership, privacy and identity management and some institutions such as the European Commission have started to provide measures for controlling this. The impressive access to OSN from ever smarter mobile devices, as well as the growth of mobile- specific SN services (e.g. WhatsApp) have further stimulated the mobile industry that is already starving for new attractive services (RCS 1). In this context OMA 2 as mobile industry forum has recently promoted the SNEW specifications that can leverage network services such as user identity and native interoperability of mobile networks (the approach promoted by “federated social networks”). -
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. -
Chazen Society Fellow Interest Paper Orkut V. Facebook: the Battle for Brazil
Chazen Society Fellow Interest Paper Orkut v. Facebook: The Battle for Brazil LAUREN FRASCA MBA ’10 When it comes to stereotypes about Brazilians – that they are a fun-loving people who love to dance samba, wear tiny bathing suits, and raise their pro soccer players to the levels of demi-gods – only one, the idea that they hold human connection in high esteem, seems to be born out by concrete data. Brazilians are among the savviest social networkers in the world, by almost all engagement measures. Nearly 80 percent of Internet users in Brazil (a group itself expected to grow by almost 50 percent over the next three years1) are engaged in social networking – a global high. And these users are highly active, logging an average of 6.3 hours on social networks and 1,220 page views per month per Internet user – a rate second only to Russia, and almost double the worldwide average of 3.7 hours.2 It is precisely this broad, highly engaged audience that makes Brazil the hotly contested ground it is today, with the dominant social networking Web site, Google’s Orkut, facing stiff competition from Facebook, the leading aggregate Web site worldwide. Social Network Services Though social networking Web sites would appear to be tools born of the 21st century, they have existed since even the earliest days of Internet-enabled home computing. Starting with bulletin board services in the early 1980s (accessed over a phone line with a modem), users and creators of these Web sites grew increasingly sophisticated, launching communities such as The WELL (1985), Geocities (1994), and Tripod (1995). -
2010 Nonprofit Social Network Benchmark Report
April 2010 Nonprofit Social Network Benchmark Report www.nonprofitsocialnetworksurvey.com www.nten.org www.commonknow.com www.theport.com Introduction NTEN, Common Knowledge, and ThePort Network offer this second annual installment of the Nonprofit Social Networking Benchmark Report. This report’s objective is to provide nonprofits with insights and trends surrounding social networking technology as part of nonprofit organizations’ marketing, communications, fundraising, and program house social network services. Social networking community built on Between February 3 and March 15, 2010, a nonprofit’s own 1,173 nonprofit professionals responded to website. Term derived a survey about their organization’s use of from direct mail online social networks. house lists. Two groups of questions were posed to survey participants: commercial 1. Tells us about your use of commercial social network social networks such as Facebook, Twitter, An online community LinkedIn, and others. owned and operated by a corporation. 2. Tell us about your work building and Popular examples using social networks on your own include Facebook and websites, called house social networks . MySpace. Survey respondents represented small, medium and large nonprofits and all nonprofit segments: Arts & Culture, Association, Education, Environment & Animals, Health & Healthcare, Human Services, International, Public & Societal Benefit, Religious and others (See Appendix A for more details). www.nonprofitsocialnetworksurvey.com 1 Executive Summary Commercial Social Networks Nonprofits continued to increase their use of commercial social networks over 2009 and early 2010 with Facebook and Twitter proving to be the preferred networks. LinkedIn and YouTube held steady, but MySpace lost significant ground. The following are the key excerpts from this section: • Facebook is still used by more nonprofits than any other commercial social network with 86% of nonprofits indicating that they have a presence on this network. -
THE NETWORK CITY Paul Craven Barry Wellman Research Paper No. 59 Centre for Urban and Community Studies Department of Sociology
THE NETWORK CITY Paul Craven Barry Wellman Research Paper No. 59 Centre for Urban and Community Studies and Department of Sociology University of Toronto July, 1973 To appear in a special issue on "The Community" of Sociological Inquiry. ABSTRACT The network approach to urban studies can be differentiated from other approaches by its insistence on the primacy of structures of interpersonal linkages, rather than the classification of social units according to their individual characteristics. Network analysis is an approach, leading to the formulation of particular kinds of questions, such as "who is linked to whom?" and "what is the structure and content of their relational network;" at the same time it is a methodology for their investigation. Following a discussion of network analytic methods, several of the key issues in urban studies are investigated from this perspective. Interpersonal ties in the city, migration, resource allocation, neighbor hood and connnunity are examined in terms of the network structures and processes that order and integrat~ urban activities. These structures and processes reveal U1emselves to be ever more complex and extensive at each level of the investigation. A view of the city itself as a network of networks is proposed. It is the organization of urban life by networks that makes the scale and diversity of the city a source of strength rather than chaos, while it is precisely that scale and diversity which maKes the complex and widely-ramified network structures possible. The flexibility inherent in network structures can accommodate a variety of situations, while variations in the content and intensity of network linkages allows for the co-ordination and integration of widely different people and activities. -
Formalist and Relationalist Theory in Social Network Analysis
Formalist and Relationalist Theory in Social Network Analysis Emily Erikson Yale University 17 March 2011 Draft Acknowledgements: I would like to thank Peter Bearman, Scott Boorman, Richard Lachmann, David Stark, Nicholas Wilson, the participants of Boston University’s Society, Politics & Culture Workshop, and Yale University’s Comparative Research Workshop for their helpful comments. s Abstract: There is a widespread understanding that social networks are relationalist. In this paper, I suggest an alternative view that relationalism is only one theoretical perspective in network analysis. Relationalism, as currently defined, rejects essentialism, a priori categories, and insists upon the intersubjectivity of experience and meaning, as well as the importance of the content of interactions and their historical setting. Formalism is based on a structuralist interpretation of the theoretical works of Georg Simmel. Simmel based his theory on a Neo-Kantian program of identifying a priori categories of relational types and patterns that operate independently of cultural content or historical setting. Formalism and relationalism are therefore entirely distinct from each other. Yet both are internally consistent theoretical perspectives. The contrast between the two plays out in their approaches to culture, meaning, agency, and generalizability. In this paper, I distinguish the two theoretical strains. 2 Since its inception in the 1930s, social network research has become an increasingly vibrant part of sociology inquiry. The field has grown tremendously over the last few decades: new journals and conferences have been created, programs and concentrations in social network analysis have been created in institutions in both North America and Europe, and large numbers of scholars have been attracted to the field from across a wide disciplinary array, including sociology, anthropology, management sciences, computer science, biology, mathematics, and physics. -
Columbia University Center Fororal History
Columbia University Center for Oral History TEN-YEAR REPORT “The great strength of oral history is its ability to record memories in a way that honors the dignity and integrity of ordinary people.” —Mary Marshall Clark, Director, Columbia Center for Oral History Letter from the Director .............................. 1 CCOH Mission and History ............................ 3 Research ........................................ 5 September 11, 2001, Oral History Projects . 5 After the Fall, CCOH Director Book . 7 Apollo Theater Oral History Project . 7 Guantánamo Bay Oral History Project Video Interviews in London, England . 8 Atlantic Philanthropies Oral History Project . 8 Council on Foreign Relations Oral History Project . 9 Elizabeth Murray Oral History of Women in the Visual Arts . 9 Guantánamo Bay Oral History Project . 9 Rule of Law Oral History Project . 10 United Nations Intellectual History Project . 10 Biographical Interviews . 10 John W. Kluge (1914–2010) . 10 William T. Golden (1909–2007) . 11 Robert P. DeVecchi . 11 Archive ......................................... 13 Oral History Collections Portal . 13 CCOH’s New Website . 13 Digital Exhibitions . 14 Preservation . 15 Education ........................................ 17 Oral History Master of Arts . 17 Summer Institute . 17 Workshops and Events . 19 Conference Presentations . 21 Consultations . 21 Oral History Training for Educators and Human Rights Activists . 22 Online Outreach . 22 Publications ...................................... 23 Staff, Supporters, and Advisory Board .................... 25 Staff and Interviewers . 25 Advisory Committee . 26 Supporters . 27 Contact Us ............................ inside back cover 1 Letter from the Director Ten years ago, in June 2001, I was named director of the Oral History Research Office . Having worked for some years at Columbia, I knew my way around and looked forward to some time to plan the future .