Graduate Programs with Emphasis in Social Network Analysis

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Masters in Language and Communication
Department of Linguistics, University of Georgetown University
Ticknor, Kathryn
The M.A. in Language and Communication is a professionally-oriented program within the Linguistics Department at Georgetown University. This program cultivates strong research and analytical abilities in sociolinguistics, specifically discourse analysis (i.e. narrative analysis and cross cultural communication), variation analysis, and pragmatics. The program is designed to link these theories to practice in a range of professional fields.


LINKS Center for organizational social network analysis
Department of Management, University of U of Kentucky
Borgatti, Steve
The Management Department at the University of Kentucky focuses on social networks, both in terms of faculty research and in terms of the Ph.D. program. In addition, we run the LINKS center for organizational social network analysis. The LINKS center sponsors research, puts on yearly workshops, runs an annual conference (ION), and sponsors talks and best-paper awards.

Graduate Program in Communication
Department of Communication, University of University at Buffalo (SUNY)
Barnett, George
 The Department of Communication at the University at Buffalo (SUNY) offers a quantitative behavioral science based graduate program. Its foci include social influence, health, intercultural/international and computer-mediated communication. The faculty studies various aspects of social and communication networks including Frank Tutzauer (mathematical models of social networks), Joseph Woelfel (neural networks), Michael Stefanone (computer-mediated networks), Tom Feeley (social influence) and George Barnett (international networks).


Complex Systems and Computational Social Science (CSCS)
Payne, Diane
Department of UCD Geary Institute, University of University College Dublinss Complex Systems and Computational Social Sciences
Thematic PhD Programme
University College Dublin
UCD Geary Institute invites applications for September 2009 for a new Thematic Doctoral Programme in Complex Systems and Computational Social Sciences. (CSCS)

The CSCS PhD programme is a four year thematic, structured programme commencing in the Academic Year 2009/2010. Staff involved in the programme are drawn from a variety of research groups in both UCD Geary Institute and UCD Complex and Adaptive Systems Laboratory, as well as from the Schools of Business, Mathematical Sciences, Computer Science and Informatics, Engineering, Economics, Politics and International Relations and Sociology.

The programme incorporates a range of taught modules, followed by a program of original research leading to the award of Doctoral degree by research. CSCS students may also participate in short, external internships during the four year programme.

Entry to the CSCS programme requires an undergraduate degree in suitable disciplines in the social sciences, mathematical and/or computer science or closely related areas. Applicants from other disciplines may also be admitted, under certain circumstances .

Further details, including application procedure, are available at http://geary.ucd.ie/cscs/.


 Interdisciplinary Graduate Studies
Department of Graduate Studies, University of University of British Columbia Okanagan
Jatel, Nelson
Interdisciplinary Graduate Studies (IGS) ees Offered: M.A., M.Sc., & Ph.D.

UBC Okanagan offers interdisciplinary graduate degrees across a wide range of program options from the humanities and creative arts to social and natural sciences. Interdisciplinary studies are thesis-based programs. Students may chose to complete a themed or individualized program.

Link: http://www.ubc.ca/okanagan/gradstudies/advising/IGS.html


Program in Sociology, Social Network Specialization
Department of Department of Sociology, University of University of California, Irvine
Butts, Carter
The University of California at Irvine is home to one of the premier research groups in the expanding field of social networks. With faculty in Sociology, Anthropology, Economics, Criminology, Law, and Society, Information and Computer Sciences, and the Graduate School of Management, UCI maintains a large and diverse community of network researchers with a wide range of substantive interests. The School of Social Sciences has had a Graduate Program in Social Networks for 20 years (it has granted 46 Ph.D.s since the mid 1980s). With an active community and numerous opportunities for research collaborations, UCI is an ideal place to study social networks.

The Sociology Department is a major hub of social network activity at UCI. We offer a unified program of graduate training in social networks, with a field specialization in the area and a core curriculum covering theoretical foundations, methodological approaches, and substantive applications. We also host a regular colloquium series and weekly network research meetings where graduate students and faculty discuss their on-going research projects. Graduate training in the field is supported by faculty in several departments and the Institute for Mathematical Behavioral Sciences.

Current social network research by faculty and graduate students covers a wide array of substantive topics, including: networks among responders to disasters; socio-spatial features of networks in high crime neighborhoods; effects of economic and social transformations on kinship and support networks in rural villages; social networks of immigrants; global city networks; international trade networks; and homophily in professional networks, to name a few. UCI served as the founding home to the flagship journal in the field, Social Networks, with Lin Freeman as editor. In recent years the social network group has hosted a number of special events including symposia, workshops, and co-sponsorship of international meetings (including the XXV International Sunbelt Social Network Conference, and the US/Japan Mathematical Sociology Conference).

Social Network Analysis Courses

Kathryn Social Network Analysis
Department of Culture, Communication and Technology, University of Georgetown University
Ticknor, Kathryn
 Social network analysis is both an approach to understanding social structure and a method of analysis. Students in this course will learn social networks theory as well as how to do network analysis. The social network approach has been used to study a variety of topics, from the Medici family's business and marriage relations in Florence in the Middle Ages to terrorist networks today.

There are three parts to this class: instruction, practice, and theory. This course will review classic network literature providing examples of the implementation of the network approach to a variety of topics. These substantive articles will be accompanied by supplemental readings that clarify the network concepts and techniques used by the authors, which include mathematical techniques using matrices and graphs.

No background in network methods or advanced mathematics is required to take this class; all mathematical concepts necessary to understand the models covered will be reviewed. Practical exercises will be assigned as a compliment to the reading to illustrate concepts. Students will work through problem exercises using Microsoft Excel and the social network analysis software package, UCINET.


Knowledge Management
Department of Culture, Communication and Technology, University of Georgetown University
Ticknor, Kathryn
In today's world the sheer amount of data and information created by and accessible to individuals and organizations overwhelm us. But, the real challenge is the continual struggle to transform these into usable and reusable knowledge. This challenge faces all organizations - corporate enterprises, non-profits, educational institutions and government agencies. This course reaches behind the current fads regarding organizational knowledge management to explore the theoretical foundation for knowledge, its meaning and value, as well as policies and approaches for building capabilities to manage knowledge within and across organizational boundaries. By the end of this course, students will be able to articulate key knowledge management concepts, issues and trends regarding a variety of related topics, which include: Nature and topology of knowledge Knowledge economy Theory, policies, practices and problems for: - Knowledge capture/acquisition - e.g., mentoring, storytelling, social network analysis - Knowledge conversion/transfer e.g., documentation, cognitive learning, collaborative sharing and situated learning - Knowledge reuse/application- e.g., accessibility, infrastructure and reliability - Research strategies and methods - Roles in knowledge management - e.g., managers, intermediaries, facilitators, seekers, practitioners.


SOC 300 Social Network Analysis
Department of Social Sciences, University of Saint Thomas Aquinas College
McCulloh, Ian  
This course will familiarize students with basic concepts in social network analysis. Topics include graph theory, measures of social networks, collecting network data, subgroup analysis, blockmodeling, the social psychology of connections, organizational theory, and statistical testing of networks. This is an applied course that will require students to construct, test, and analyze social networks of local organizations as well as terrorist groups in Iraq.


PL 470 Basic Social Network Analysis
Department of Behavioral Sciences and Leadership, University of U.S. Military Academy
McCulloh, Ian
 This course will familiarize students with basic concepts in social network analysis. Topics include graph theory, measures of social networks, collectin network data, subgroup analysis, blockmodeling, the social psychology of connections, organizational theory, and statistical testing of networks. This is an applied course that will require students to construct, test, and analyze social networks of local organizations as well as terrorist groups in Iraq.


 MA488 Advanced Social Network Analysis
Department of Mathematical Scienes, University of U.S. Military Academy
McCulloh, Ian
This course investigates mathematical topics in social network analysis. Topics include exploring dyad/triad census, QAP, ergm, actor-oriented nework models, longitudinal network analysis, link probability model, and dependence graphs. Students are expected to code algorithms for analysis in a programming environment of their choice.


Theory, methods and applications of social networks. Dynamic Analysis with SIENA (2 ECTS)
Department of ropologia social i cultural, University of Universitat Autònoma de Barcelona
Molina, Jose Luis
 This summer course is intended to graduate students, researchers or professionals interested in an introduction to the theory and methods of social networks and especially in dynamic analysis of social networks with SIENA. The sessions will be both in Spanish and English, except the SIENA workshop, mainly in English. At the end of each session participants should complete a task and send it to professors. The last session is devoted to presentations by participants. The participants who complete the scheduled tasks will get an official recognition of credits.


Theory, Methods and Applications of Social Networks. The measurement of personal networks and the elicitation of hidden populations (2 ECTS)
Department of Social and Cultural GRAFO), University of Universitat Autonoma de Barcelona
Molina, Jose Luis
The aim of this 6th edition of the summer course is to enable graduate students in the social sciences to create, compare and critique personal network research designs, with special attention to the issue of hidden populations. On the first day, we will discuss the basic definitions and central concepts in personal network research and will briefly relate personal networks with various theoretical streams in the social sciences. This will give students an understanding of the requirements that researchers may pose to their instruments. We will then introduce the basic steps of measurement of personal networks in survey research. On the second day, we will focus on the name generators. Students will be introduced to the variety of name generators used in social sciences, which will be compared with respect to contents, the characteristics of the measured networks and ties, the reliability and validity of the measures, and respondent burden. Many empirical applications will be discussed during this session. In the third session, we will discuss the measurement of basic name interpreters, such as tie strength, roles and contexts. The fourth session is devoted to methods for estimating hidden populations. Finally an international seminar on personal networks will end the course.


Network Theory
Department of Sociology, University of University of California, Irvine
Butts, Carter
This course provides an introduction to the basic principles and classic themes dominating theoretical work in the social network field. Specific topics covered include baseline network models, homophily and propinquity, theories of exchange and power, balance theory, models of diffusion and social influence, equivalence, and cohesion. The approach taken to the material is hands-on: homework assignments focus on the active use of theory to make specific predictions about social structures and processes. By the end of the class, each student should understand the basic concepts used to represent relational structure, should be familiar with several of the major theoretical programmes in the network field, and should be able to apply these theories to novel scientific problems.


Networks and Organizations
Department of Sociology, University of University of California, Irvine
Butts, Carter
 Structural perspectives have long played a major role in the study of organizations, and organizational research has provided a corresponding impetus for the development of modern network analysis. This course will provide an introduction to some of the major areas of research at the intersection of these two fields. The approach taken is interdisciplinary, bringing together work in sociology, management science, organizational behavior, and economics; emphasis is on predictive (i.e., scientific) research, but some normative (i.e., engineering) issues will be considered as well. Specific topics covered include firm size, organizational design, diffusion and influence processes, competition, exchange processes, and organizational learning. In addition to reviewing relevant literature, students in this class develop their own research projects relating to the course topic, and opportunities are provided to present this work to the class as a whole.


Networks and Information Transmission
Department of Sociology, University of University of California, Irvine
Butts, Carter
 From its earliest beginnings, communication -- and, in particular, the flow of information -- has been one of the core themes of the social network field. This course provides an introduction to current and past research on communication and information transmission within interpersonal networks. Coverage anges from the micro-processes involved in information acquisition and recall to the macro-level phenomena of diffusion at the population level, with the meso-level process of local communication also being considered. Specific topics covered include cognitive and affective effects on communication, information corruption due to serial transmission, rumors and disasters, memetics, and information seeking behavior. Organizational and policy implications are also discussed. In addition to reviewing relevant literature, students in this class develop their own research projects relating to the course topic, and opportunities are provided to present this work to the class as a whole.


Informant Accuracy
Department of Sociology, University of University of California, Irvine
Butts, Carter
 Ethnographic, archival, and survey research frequently depends upon individual accounts to reconstruct historical events, cultural conventions, past behavior, social structure, and the like. In such settings, the sources of these accounts (i.e., informants) act as the ``measurement devices'' through which the social scientist probes the system under study. While human informants can yield information which is difficult or impossible to obtain through alternate means, their accounts are subject to various kinds of error. Understanding the determinants of such error is thus of substantial importance in conducting informant-based research. This class surveys key findings from the literature on informant accuracy, and introduces a number of methods for estimating and reducing the impact of error on subsequent analyses. Specific applications examined include cultural domain analysis, the estimation of competency, and network inference.


Social Networks
Department of Sociology, University of University of California, Irvine
Butts, Carter
 Study of the causes and consequences of patterned interactions among social entities is the domain of the social network field. This course provides a hands-on introduction to some of the basic concepts and methods of network analysis, as well as a sampling of classic and modern research findings regarding the properties of social networks. By the end of this course, each student will have an understanding of the above topics, as well as experience with the collection and analysis of network data using modern computational tools. The course will culminate in a group research project, in which each student will be involved in the collection, analysis, and presentation of network data on a topic of their choosing.


Theory & Applications of SNA
Department of Government, University of University of Essex
Christopoulos, Dimitrios
Course Content
This course is aimed at postgraduate researchers and practitioners in the social and political sciences. It is intended as an intermediary workshop for those having attained an elementary understanding of the methodology of Social Network Analysis and wishing to develop and test hypotheses in their respective fields. A strong emphasis is placed on the theoretical insights offered through the application of graph theoretical perspectives to social science research and the opportunities network analysis offers for exploring novel hypotheses.
Course Objectives In this course we:
  • develop the theoretical concepts underlying valid network analysis,
  • examine methodological tools for the analysis of networks in social science research,
  • examine methodological innovations for the testing of hypotheses employing SNA,
  • demonstrate a number of different statistical packages that will allow for the analysis of network statistics,
  • explore strategies for identifying efficiency gains through intervention in network structure,
  • demonstrate the effective graphic representation of relational ties,
  • demonstrate ways of triangulating SNA with other quantitative and qualitative social science methods.

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