Inquiry and learning into social networks, organizational network analysis, and the relationships among people and systems in complex organizations and networks.
Professor Katherine Stovel
Winter 2007, U Washington
This seminar is intended as a theoretical and analytical
introduction to structural network analysis.
Man zieht in gute Viertel, schickt die Kinder auf Privatschulen, achtet auf Stil und Manieren: Das Bürgertum grenzt sich ab – und erschwert Menschen aus den unteren Schichten den Aufstieg.
Network Workbench: A Large-Scale Network Analysis, Modeling and Visualization Toolkit for Biomedical, Social Science and Physics Research.This project will design, evaluate, and operate a unique distributed, shared resources environment for large-scale ne
Social Network Analysis Workshop at Sunbelt Conference in San Diego -- http://is.gd/3RP7 (via @valdiskrebs) [from http://twitter.com/jomiralb/statuses/1216833459]
NetMiner is an innovative software tool for Exploratory Analysis and Visualization of Network Data. NetMiner allows you to explore your network data visually and interactively, and helps you to detect underlying patterns and structures of the network
Without much surprise there has been significant movement within some of the social networks over the course of the last year. Brian Chappell from Ignite Social Media has put together a comprehensive report based on data from all major social networks existing on the web.
A range of tools for social network analysis, including node and graph-level indices, structural distance and covariance methods, structural equivalence detection, p* modeling, random graph generation, and 2D/3D network visualization.
SIENA is a program for the statistical analysis of network data, with the focus on social networks.
SIENA is designed for analyzing various types of data as dependent variables:
Longitudinal network data,
Longitudinal data of networks and behavior,
Cross-sectional network data.
Social networks are structures of relations between social actors - e.g., friendship between individuals, collaboration between companies, trade between countries, etc. They are important both in themselves and for explaining a variety of actor-dependent characteristics (behavioural tendencies, attitudes, performance, etc.) Particularly interesting is the two-way influence between relational networks and individual actions and outcomes. The data structure of social networks, where the usual statistical assumption of independent cases is totally implausible, poses special requirements for data analysis.
This course presents a number of important data analysis methods for social networks.
The material presented at this website is too extensive for the course. Only a selection of this will be treated.
The course is about five main topics:
1. Centrality and other positional characteristics of actors.
2. Concepts of positional equivalence.
3. The exponential random graph model (ERGM), a statistical model for single observations of networks.
4. Stochastic actor-based models for network dynamics (i.e., for analysing longitudinal network data).
5. Stochastic actor-based models for the simultaneous dynamics of networks and behaviour (which here is a term referring generally to changeable actor characteristics such as behavioural tendencies or performance).
The main research focus of the Social Computing Laboratory at HP Labs is harvesting the collective intelligence of groups of people to optimize the interaction between users and information. HP Labs is the advanced research center for Hewlett-Packard..
NetBase article comparing late night talk show comedians using a brand passion index graphic. Social Media Analysis of top comedians including David Letterman, Jay Leno, Seth Meyers, Conan O’Brien, Jon Stewart and Stephen Colbert.
This all began with an introductory presentation about social network analysis to a group of medical students. What better way to grab their attention than with attractive, fake doctors having sex on television? Naturally this led to the dense network … Continue reading →
This all began with an introductory presentation about social network analysis to a group of medical students. What better way to grab their attention than with attractive, fake doctors having sex on television? Naturally this led to the dense network … Continue reading →
H. Nguyen, D. Bozhkov, Z. Ahmadi, N. Nguyen, und T. Doan. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM, (Juli 2022)