ICPSR Summer Program – Analyzing Social Networks: An Introduction (Aug 8-12, 2016 at UNC-Chapel Hill)

The Odum Institute at the University of North Carolina at Chapel Hill offer joint summer courses with the Inter-university Consortium for Political and Social Research (ICPSR) as part of the ICPSR Summer Program in Quantitative Methods of Social Research. In Chapel Hill on August 8-12, 2016, Doug Steinley from the University of Missouri will teach Analyzing Social Networks: An Introduction.

This course will present an introduction to concepts, methods, and applications of social network analysis drawn from the social and behavioral sciences. The primary focus of these methods is the analysis of relational data measured on groups of social actors. Topics include an introduction to graph theory and the use of directed graphs to study actor interrelations; structural and locational properties of actors, such as centrality, prestige, and prominence; subgroups and cliques; equivalence of actors, including structural equivalence, blockmodels, and an introduction to relational algebras; an introduction to local analyses, including dyadic and triadic analyses; and an introduction to statistical analyses, using models such as p1 and exponential random graph models. The workshop will use several common software packages for network analysis: UCINET, Pajek, NetDraw, and STOCNET.

Visit the ICPSR Summer Program in Quantitative Methods of Social Research website for more information on other courses and to register.

Data Matters: Data Science Short Course Series (Aug. 8-12, 2016 at NC State)

In partnership with the Odum Institute for Research in Social Science at UNC-Chapel Hill and the National Consortium for Data Science (NCDS), the Data Science Initiative at NC State is sponsoring Data Matters: Data Science Short Course Series, a week-long series of classes for faculty, staff, students, researchers, and others who wish to increase their skills in data analytics and integrate data science methods into their research designs and skill sets. Scholars, analysts, and researchers from all disciplines and industries are welcome. Both one- and two-day courses will be offered; participants are welcome to register for one, two, or three classes.

Course offerings include Introduction to Data Science, Introduction to Data Visualization, Introduction to Data Science using R, Working with Messy Data, Open(ing) Data, Programming in R, Introduction to Machine Learning, Collecting, Classifying and Analyzing Textual Data, and Data Curation.

Visit the NC State Data Science Initiative website for more information and to register.

Upcoming Lecture — “Inferring Community Structure in Networks with Metadata” with Aaron Clauset (February 23, 2016)

Aaron Clauset from University of Colorado at Boulder will give a specially scheduled Applied Mathematics Colloquium on Tuesday February 23, 2016 at 4 pm in Davie Hall 0112 entitled “Inferring community structure in networks with metadata.” See the abstract for the talk below.

Abstract: For many networks of scientific interest we know both the connections of the network and information about the network nodes, such as the age or gender of individuals in a social network, geographic location of nodes in the Internet, or cellular function of nodes in a gene regulatory network. In this talk, I’ll show how this “metadata” can be used to improve our analysis and understanding of network structure. I’ll focus in particular on the problem of community detection in networks and present a mathematically principled approach, based on a generalization of the stochastic block model, that combines a network and its metadata to detect communities more accurately than can be done with either alone. Crucially, the method does not assume that the metadata are correlated with the communities we are trying to find. Instead the method learns whether a correlation exists and correctly uses or ignores the metadata depending on whether they contain useful information. The learned correlations are also of interest in their own right, allowing us to make predictions about the community membership of nodes whose network connections are unknown. I’ll demonstrate the model on synthetic networks with known structure, where the method performs better than any algorithm without metadata, and on real-world networks, large and small, drawn from social, biological, and technological domains.

 

Data Matters: Data Science Short Course Series (June 20-24, 2016)

The Data Matters is a week-long series of one and two-day courses aimed at professionals in business, research, and government. The short course series is sponsored by the National Consortium for Data Science (NCDS), the Renaissance Computing Institute (RENCI), and the Odum Institute for Research in Social Science. Organizations struggling to stay afloat in the data deluge, those grappling daily with large, complex data, and anyone who wants to capitalize on the opportunities of big data should consider attending the short course series.

The workshop series will be held on June 20-24, 2016 at the Friday Center for Continuing Education in Chapel Hill, NC. Highly qualified instructors from across the country teach courses on topics such as information visualization, data curation, R, health informatics, open data, machine learning, social network analysis, and more.

For more information on course descriptions, fees, and registration visit datamatters.org.

Upcoming Lecture — “A Network Formation Model Based on Subgraphs” with Arun Chandrasekhar (Nov. 20, 2015)

The Economics Department at UNC will sponsor a talk by Arun Chandrasekhar from Stanford on November 20, 2015 from 1:30 p.m. to 3:00 p.m. in Gardner Hall, Room 211. The title of the talk is “A network formation model based on subgraphs” and is based on a working paper written with Matthew Jackson. The working paper can be found here.

For more information on events hosted by the UNC Economics Department, see their calendar.

INSNA Sunbelt Conference 2016

The XXXVI Sunbelt Social Networks Conference will be held on April 5 – 10, 2016 in Newport Beach, California. This conference is the official annual conference of the International Network for Social Network Analysis (INSNA). The Sunbelt conference provides an interdisciplinary venue for social scientists, mathematicians, computer scientists, ethnologists, epidemiologists, organizational theorists, public health experts, and others to present current work in the area of social networks.

For more information about the conference and calls for submissions, visit the 2016 Sunbelt Conference website.

Data Matters Workshop Series (June 23-27)

The Data Matters: Data Science Summer Workshop Series, sponsored by the National Consortium for Data Science (NCDS), data-matters-story-imagethe Renaissance Computing Institute (RENCI), and the Odum Institute for Research in Social Science, is a week-long series of classes for researchers, data analysts, and other individuals who wish to increase their skills in data studies and integrate data science methods into their research designs and skill sets. Scholars, analysts, and researchers from all disciplines and industries are welcome.

The workshop series will be held on June 23-27, 2014 at the Friday Center for Continuing Education in Chapel Hill, NC and offers both one-day and two-day courses. Courses offered at the workshop will cover a variety of data topics including social network analysis, large-scale data networks, managing big data, data visualization, machine learning, data management and analysis tools, and predictive analysis.

For more information on course descriptions, fees, and registration click here.

Network Analysis: Statistical Inference with Exponential Random Graph Models (May 8)

The Odum Institute will host a Network Analysis Workshop on Statistical Inference with Exponential Random Graph Models taught by Bruce Desmarais on May 8, 2014 from 10:00 a.m. to 4:00 p.m.Odum logo

Exponential Random Graph Models (ERGMs) are flexible statistical models for relational (i.e., network) data that are capable of representing and identifying an extensive range of interdependencies common in networks. Are gender, race or social class predictive of mixing patterns in a social network? Are ties in a directed network typically reciprocated? Does the network exhibit transitive triad closure? The simultaneous and stochastic manifestation of relational dependencies such as these can be identified and characterized with ERGMs. This workshop will introduce ERGM and demonstrate its application in the free and open source R statistical software. Participants will be provided with real-world network data as well as R code to apply ERGMs to that data.

Prerequisites for this course include a background in basic network analysis concepts and novice experience with the R statistical software.

For more information or to register for this course click here.

Probability Seminar — “Dynamics of Retweeting on Twitter” (Feb. 27)

The Department of Statistics and Operations Research will sponsor a probability seminar with Tauhid Zaman on the “Dynamics of Retweeting on Twitter.”  This seminar will be held on February 27 from 4:15 to 5:15 in Hanes 130. Tauhid Zaman is an Assistant Professor of Operations Management at the MIT Sloan School of Management. His research focuses on utilizing large-scale data from online social networks such as Facebook and Twitter to develop predictive models for user behavior and optimize business operations.

Upcoming Lecture — “Machine Learning and Causal Inference: A Modular Approach to Assessing the Effects of the London Bombings of 2005” with Jake Bowers (Oct. 25)

The American Politics Research Group (APRG) at UNC will sponsor a presentation by Jake Bowers from the University of Illinois on Friday, October 25th from noon to 1:00 p.m. in Hamilton 355. Dr. Bowers will present “Machine Learning and Causal Inference: A Modular Approach to Assessing the Effects of the London Bombings of 2005.” A copy of the paper can be found here.

For more information on upcoming APRG seminars, see the George Rabinowitz Seminar schedule.