NETWORK ANALYSIS Sociology 920:570:01 Paul Mclean
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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. -
Methods Exam Reading List August 2016 Creswell
Methods Exam Reading List August 2016 Creswell, John. 2014. Research Design: Qualitative, Quantitative and Mixed Methods Approaches. Sage 94th edition). Emerson, Robert, Rachel Fretz and Linda Shaw. 2011. Writing Ethnographic Fieldnotes (Second Edition). Univ. of Chicago Press. Ragin, Charles. 1987. The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies. Univ. of California Press. Liamputtong, Pranee. 2011. Focus Group Methodology Principle and Practice. Sage Publishing. Weiss, Robert. 1994. Learning from Strangers: The Art and Methods of Qualitative Interview Studies. Free Press. Chamblis, D.F. and Schutt, R.K. 2016. Making Sense of the Social World: Methods of Investigation. Los Angeles: Sage. Chapter 11: Unobtrusive Measures. Groves, R., F. Fowler, M. Couper, J Lepkowski, E. Singer and R Tourangeau. 2004. Survey Methodology. Wiley Maines, D.R. 1993. “Narrative’s Moment and Sociology’s Phenomena: Toward a Narrative Sociology.” The Sociological Quarterly 34(1): 17-38. Pampel, F.C. 2000. Logistic Regression: A Primer. Thousand Oaks: Sage Publication. Small, Mario. 2011. How to Conduct a Mixed Methods Study: Recent Trends in a Rapidly Growing Literature. Annual Review of Sociology 37:57-86. Tight, M. 2015. Case Studies. Sage Publications. Corbin, Juliet A., and Anselm Strauss. 2015. Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. Thousand Oaks, CA: Sage. Lieberson, Stanley. 1985. Making It Count: The Improvement of Social Research and Theory. Berkeley, CA: University of California Press. 1 Ragin, Charles C., and Howard S. Becker. 1992. What is a Case? Exploring the Foundations of Social Inquiry. New York: Cambridge University Press. Stinchcombe, Arthur L. 1968. Constructing Social Theories. New York: Harcourt, Brace & World. -
CURRICULUM VITAE ANN MISCHE Department of Sociology Rutgers, the State University of New Jersey 54 Joyce Kilmer Avenue, Pisc
CURRICULUM VITAE ANN MISCHE Department of Sociology Home address: Rutgers, The State University of New Jersey 229 S. 3rd Ave. 54 Joyce Kilmer Avenue, Piscataway, NJ 08854 Highland Park, NJ 08904 phone: 732-445-6598 home phone: 732-846-2764 fax: 732-445-0974 email: [email protected] ACADEMIC POSITIONS Rutgers, The State University of New Jersey, Associate Professor (with tenure), Department of Sociology, 2005-present; Assistant Professor, 1999-2005. Harvard University, Department of Sociology, Visiting Scholar, fall 2002. University of Melbourne, Australia, School of Behavioural Sciences, Research Fellow, summers 1998- 2001. Center for the Critical Analysis of Contemporary Culture, Rutgers University, Associate Fellow, 1999-2000. Columbia University, Paul F. Lazersfeld Post-doctoral Research Fellow, 1998-99; Visiting Scholar, 1996-98 and 1994-95. Pontifícia Universidade Católica, São Paulo, Brazil, Visiting Researcher, Social Psychology, 1994-96. EDUCATION New School for Social Research, Graduate Faculty of Political and Social Sciences, Ph.D. in Sociology, 1998; M.A. in Sociology, 1992. Yale University, B.A. in Philosophy with distinction in the major, 1986. AREAS OF INTEREST Sociology of culture, social movements, political sociology, social networks, organizations, sociological theory. SCHOLARLY PUBLICATIONS Mische, Ann. 2003. “Cross-Talk in Movements: Rethinking the Culture-Network Link.” Pp. 258- 280 in Social Movements and Networks: Relational Approaches to Collective Action, edited by Mario Diani and Doug McAdam, Oxford University Press. 2 Mische, Ann. 2001. “Juggling Multiple Futures: Personal and Collective Project-formation among Brazilian Youth Leaders.” Pp.137-159 in Leadership and Social Movements, edited by Alan Johnson, Colin Barker, and Michael Lavalette, Manchester University Press. -
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. -
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 -
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”). -
Studying Personal Communities in East York
STUDYING PERSONAL COMMUNITIES IN EAST YORK Barry Wellman Research Paper No. 128 Centre for Urban and Community Studies University of Toronto April, 1982 ISSN: 0316-0068 ISBN: 0-7727-1288-3 Reprinted July 1982 ABSTRACT Network analysis has contributed to the study of community through its focus on structured social relationships and its de-emphasis of local solidarities. Yet the initial surveys of community networks were limited in scope and findings. Our research group is now using network analysis as a comprehensive structural approach to studying the place of community networks within large-scale divisions of labour. This paper reports on the analytical concerns, research design and preliminary findings of our new East York study of "personal communities". - 11 - STUDYING PERSONAL COMMUNITIES IN EAST YORK 1 OLD AND NEW CAMPAIGNS Generals often want to refight their last war; academics often want to redo their last study. The reasons are the same. The passage of time has made them aware of mistakes in strategy, preparations and analysis. New concepts and tools have come along to make the job easier. Others looking at the same events now claim to know better. If only we could do the job again! With such thoughts in mind, I want to look at where network analyses of communities have come from and where they are likely to go. However, I propose to spend less time in refighting the past (in part, because the battles have been successful) than in proposing strategic objectives for the present and future. In this paper, I take stock of the current state of knowledge in three ways: First, I relate community network studies to fundamental concerns of both social network analysis and urban sociology. -
THE TRUTH GAME (Silvan Mühlemann, Geneva 2019)
THE TRUTH GAME (Silvan Mühlemann, Geneva 2019) 1 I. DEFENDING AXIOMATIC-DEDUCTIVE SCIENCE ( ) 1. CHOOSING ONE’S AXIOMS: THE EPISTEMOLOGY OF HAPPINESS. According to Karl Popper2, science begins with falsifiable hypotheses. These hypotheses are, as explained by Ashish Dalela, chosen as a function of happiness they provide us. It is intuitively clear that happiness, not truth, is the highest goal in life. “To know the truth we must know the good, but to pick the good, we must desire that good. Ultimately, our cognition of truth depends on our desire. If that desire is modified, then the truths are modified. Similarly, happiness is produced only when the desires are fulfilled. Therefore, if you find the thing that you desire, then you have the double satisfaction of finding truth and goodness. Your brain tells you that you have found the truth, and your heart tells you that you have fulfilled your desire. If you tell a happy person that his ideas about the world are false, he will most likely ignore you, because he knows that since he is happy he must be doing something correctly, and consequently his beliefs must also be true. On the other hand, if you tell an unhappy person that he is suffering because of his false beliefs, and that he must change his beliefs in order to find happiness, he is more likely to listen to your arguments. In short, new knowledge doesn’t come when you are happy, because there is complacency whereby one’s current beliefs are accepted as true just because one is already happy and contented. -
Mathematical Modeling and Anthropology: Its Rationale, Past Successes and Future Directions
Mathematical Modeling and Anthropology: Its Rationale, Past Successes and Future Directions Dwight Read, Organizer European Meeting on Cybernetics and System Research 2002 (EMCSR 2002) April 2 - 5, 2002, University of Vienna http://www.ai.univie.ac.at/emcsr/ Abstract When anthropologists talk about their discipline as a holistic study of human societies, particularly non-western societies, mathematics and mathematical modeling does not immediately come to mind, either to persons outside of anthropology and even to most anthropologists. What does mathematics have to do with the study of religious beliefs, ideologies, rituals, kinship and the like? Or more generally, What does mathematical modeling have to do with culture? The application of statistical methods usually makes sense to the questioner when it is explained that these methods relate to the study of human societies through examining patterns in empirical data on how people behave. What is less evident, though, is how mathematical thinking can be part of the way anthropologists reason about human societies and attempt to make sense of not just behavioral patterns, but the underlying cultural framework within which these behaviors are embedded. What is not widely recognized is the way theory in cultural anthropology and mathematical theory have been brought together, thereby constructing a dynamic interplay that helps elucidate what is meant by culture, its relationship to behavior and how the notion of culture relates to concepts and theories developed not only in anthropology but in related disciplines. The interplay is complex and its justification stems from the kind of logical inquiry that is the basis of mathematical reasoning. -
Anti-Conformism and Social Networks Alexis Poindron
Anti-conformism and Social Networks Alexis Poindron To cite this version: Alexis Poindron. Anti-conformism and Social Networks. Economics and Finance. 2016. dumas- 02102411 HAL Id: dumas-02102411 https://dumas.ccsd.cnrs.fr/dumas-02102411 Submitted on 18 Apr 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Anti-conformism and Social Networks Alexis Poindron Université Paris I Sorbonne, UFR de sciences économiques 02 Master 2 Économie Théorique et Empirique 2015-2016 Mémoire présenté et soutenu par Alexis Poindron le 17/05/2016 Sous la direction de Michel Grabisch et Agnieszka Rusinowska May 17, 2016 L’Université de paris I Panthéon Sorbonne n’entend donner aucune approbation, ni désappro- bation aux opinions émises dans ce mémoire ; elle doivent être considérées comme propres à leur auteur. 1 Contents 1 Introduction . .3 1.1 Literature review and context of this master thesis . .3 1.2 Some notations and definitions . .5 2 Generalized OWA . .6 2.1 GOWA: definitions and exemples . .6 2.2 Discussion on GOWA . .8 3 Terminal states and classes with GOWA: homogeneous framework . .9 3.1 Preliminary results . .9 3.2 List of possible terminal classes and unicity . -
An Introduction to the Social Side of Social Network Analysis Barry
An Introduction to the Social Side of Social Network Analysis Barry Wellman Director, NetLab Centre for Urban & Community Studies University of Toronto Toronto, Canada M5S 1A1 [email protected] www.chass.utoronto.ca/~wellman NetLab Barry Wellman www.chass.utoronto.ca/~wellman Possible C.S. Fallacies Only online counts Groupware NE Networkware HCI: Only two-person interactions matter Can build small world systems All ties are the same; all relationships are the same Social network software support social networks Size matters – Linked In No need to analyze networks 3 Barry Wellman www.chass.utoronto.ca/~wellman In a Sentence ––– “To Discover How A, Who is in Touch with B and C, Is Affected by the Relation Between B & C” John Barnes (anthropologist) “The Sociology is Hard. The Computer Science is Easy.” Bill Buxton (UofT, PARC, MSR) 4 Barry Wellman www.chass.utoronto.ca/~wellman What is a Social Network? Social structure as the patterned organization of network members & their relationships Old Def: When a computer network connects people or organizations, it is a social network Now ported over to more ambiguous cases: web networks; citation networks, etc. 5 Three Ways to Look at Reality Categories All Possess One or More Properties as an Aggregate of Individuals Examples: Men, Developed Countries Groups (Almost) All Densely-Knit Within Tight Boundary Thought of as a Solidary Unit (Really a Special Network) Family, Workgroup, Community Networks Set of Connected Units: People, Organizations, Networks Can Belong -
Immigrant Turnout, the Persistence of Origin Effects, and the Nature, Formation and Transmission of Political Habit
The Practice of Voting: Immigrant Turnout, the Persistence of Origin Effects, and the Nature, Formation and Transmission of Political Habit by Deanna L. Pikkov A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy in Sociology Graduate Department of Sociology University of Toronto John Myles, Supervisor Robert Andersen, Committee Member Shyon Baumann, Committee Member Richard Johnston, External Appraiser Monica Boyd, Internal Appraiser © Copyright by Deanna Pikkov (2011) Library and Archives Bibliothèque et Canada Archives Canada Published Heritage Direction du Branch Patrimoine de l'édition 395 Wellington Street 395, rue Wellington Ottawa ON K1A 0N4 Ottawa ON K1A 0N4 Canada Canada Your file Votre référence ISBN: 978-0-494-78085-5 Our file Notre référence ISBN: 978-0-494-78085-5 NOTICE: AVIS: The author has granted a non- L'auteur a accordé une licence non exclusive exclusive license allowing Library and permettant à la Bibliothèque et Archives Archives Canada to reproduce, Canada de reproduire, publier, archiver, publish, archive, preserve, conserve, sauvegarder, conserver, transmettre au public communicate to the public by par télécommunication ou par l'Internet, prêter, telecommunication or on the Internet, distribuer et vendre des thèses partout dans le loan, distrbute and sell theses monde, à des fins commerciales ou autres, sur worldwide, for commercial or non- support microforme, papier, électronique et/ou commercial purposes, in microform, autres formats. paper, electronic and/or any other formats. The author retains copyright L'auteur conserve la propriété du droit d'auteur ownership and moral rights in this et des droits moraux qui protege cette thèse. Ni thesis.