Group items tagged

The Manchester social networks group (MSNG) is a cross-disciplinary research group located in the School of Social Sciences. MSNG aims to discuss and to promote the application and development of Social Network Analysis methodology to answer important research questions in social science. The following SNA topics are of interest to the group: Data collection for social network analysis Longitudinal networks and network formation Neighbourhood and network variations in social and health outcomes Qualitative network analysis Social Networks and Social Movements Statistical modelling of social networks Visualising and describing social networks

Discourse Network Analyzer (DNA) is a Java-based application for qualitative category-based content analysis. It serves two purposes: coding statements of actors into categories, and converting these structured data into networks that are readable by UCINET, visone and other network-analytic software packages. The software can extract either bipartite (affiliation) networks or adjacency networks. It is complementary to semantic network analysis applications because it neither relies on algorithms for automatic text processing, nor does it focus on the internal meaning or mental representation of a single text or document. Instead, tags are applied to the text data by manual inspection, thus rendering it more flexible, yet at the same time more work-intensive. DNA can be used to code a large body of text documents and then convert them into graphs. The application is currently being developed, tested and heavily used in my dissertation research project on German pension politics. Updates will be posted here as soon as something has been published. If you use DNA, I would love to hear from you about your project (if possible, via the DNA-help mailing list). For more information about the software, please consult the documentation or obtain a free copy from the download page.

NodeXL is an open-source template for Excel 2007 and 2010 which provides the utility to create a hierarchical network edge list. With NodeXL, you can create a customizable hierarchical network graph and zoom, scale, or pan it for a more refined look of added data. Networks can also be imported or exported to a variety of file formats. For example, you can create a graph displaying a company's chain of command and structure of subordinate employees. NodeXL provides the convenience of eluding difficult applications, arcane file formats and programming language for creating such graphs. You can even import a list of your Twitter followers or YouTube and Flickr connections, to create graphs representing your social network.

The advantage of NodeXL, particularly for graphing Twitter communities, is it has built-in features for grabbing the data for you. Not only that the coding is clever enough to handle the data collection for mere mortals, so when you hit your rate limit NodeXL waits until it should be able to get more data. NodeXL also has "built-in connections for getting networks from Flickr, YouTube, and your local email. Additional importers for Exchange Email, Facebook, and Hyperlink networks are available".

For the past year and two I have noticed a lot of statistical analysis using #rstats /R on unstructured text generated in real time by the social network Twitter. From an analytic point of view , Google Plus is an interesting social network , as it is a social network that is new and arrived after the analytic tools are relatively refined. It is thus an interesting use case for evolution of people behavior measured globally AFTER analytic tools in text mining are evolved and we can thus measure how people behave and that behavior varies as the social network and its user interface evolves.

Bennett is a consultant on social capital and networks, and the creator of "The Hands We Shake" lecture series on how to build, grow, and sustain social capital.  He is an expert in networking strategy and social capital retention.  As a trusted adviser, he has helped start-ups, small businesses, non-profits and individuals develop a comprehensive strategy to build and cultivate their social capital.  Bennett advises his clients on how to locate and access social capital within their present networks and create a framework for future network strategy.

"Meet the Elite Business and Think-Tank Community That's Doing Its Best to Control the World The large foundations of America's industrial giants have played a truly profound - and largely overlooked - role in the shaping of modern society By Andrew Gavin Marshall Alternet, June 19, 2013 Straight to the Source For related articles and more information, please visit OCA's Politics and Democracy page. "The corporate-policy network is highly centralized, at both the level of individuals and that of organizations. Its inner circle is a tightly interwoven ensemble of politically active business leaders..." -- Academics William K. Carroll and Jean Philippe Sapinski In an article titled "The Global Corporate Elite" in the journal International Sociology, William K. Carroll and Jean Philippe Sapinski examined the relationship between the corporate elite and the emergence of a "transnational policy-planning network," beginning with its formation in the decades following World War II and speeding up in the 1970s with the creation of "global policy groups" and think tanks such as the World Economic Forum, in 1971, and the Trilateral Commission, in 1973, among many others."

If one draws links radiating outward from NATO to all of these different countries and organizations, the result is a security network that has multiple hubs and clusters - much like a map of the Internet or of planets and galaxies. This world is no longer unipolar, bipolar, or even multipolar, because the actors that matter are not single states but groups of states that are more or less densely connected. It is a multi-hub security network, in which the hubs are regional organizations of different sizes and strengths.

A number of instructors have been using NodeXL to help teaching social network analysis. It is relatively easy to use compared to many other network analysis and visualization tools, while still providing a rich set of metrics and visualization features. It is also free and integrates with Excel 2007, which many users are familiar with. This page is meant to collect information that can be useful in teaching with NodeXL.

Working with network data

NodeXL data importer for social networks!

KeyLines is a JavaScript toolkit for visualising networks. It works in all major browsers, and on all platforms, including the iPad. It uses HTML5 but also works on old versions of Internet Explorer. KeyLines is ideal for organisations who want to migrate from legacy Java, Flex or Silverlight apps to the new world of HTML5.

"Many social entrepreneurs are seeking more individualized support in the form of shared working spaces, incubators and/or accelerators that provide a mix of networking opportunities, events, funding, and mentorship in exchange for a monthly membership fee or equity stake in their company."

What makes a tweet go viral online? And what does a viral trend actually look like? Those are a couple of the questions that can be answered by a new Microsoft Research project, called Viral Search. The company's researchers are showing the project this week at an internal gathering this week in Redmond. The program crunches large amounts of data from Twitter (and potentially Facebook and other platforms in the future) to analyze and display patterns of distribution on the social network.

Time-series network data to a dynamic animation using Visone (www.leydesdorff.net/visone).

See relationships among data points: Network Diagram; Scatterplot; Matrix Chart Compare a set of values: Bar Chart; Block Histogram; Bubble Chart Track rises and falls over time: Line Graph; Stack Graph; Stack Graph for Categories See the parts of a whole: Pie Chart; Treemap; Treemap for Comparisons Analyze a text: Word Tree; Tag Cloud; Word Cloud Generator; Phrase Net See the world: Massachusetts Map; World Map; US County Map; New Jersey Map

Great news browser and filter, but very limited network visualizations

SNA package used for "ordinary" data (one line of data for each case) and for network data (two files - "nodes" and "links" )

Quantity has a quality all its own, as the saying goes. That's especially true of information. The more you've got, the more useful it becomes. Knowing sensitive facts about one person, or a dozen, may be trivially useful. But analyze the same facts about 100 million people, and you can cure diseases, win elections, or earn billions of dollars, because unpredictable insights emerge when you turn computers loose on vast storehouses of information. There's a nickname for the concept: "big data." It's one of the buzzwords of corporate executives, tech-savvy politicians, and worried civil libertarians. If you want to know what they're all talking about, then "Big Data'' is the book for you, a comprehensive and entertaining introduction to a very large topic. By analyzing huge amounts of information, it's possible to discover patterns and relationships that up to now have been invisible to us. In this way, we can find new solutions to tough problems, and opportunities we'd never otherwise have suspected.

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