INSNA home page @insna.org. Visualizing Data at the Oxford Internet Institute. Quick Guide to Social Network Analysis « SplinterNet. The last few years have seen the adoption of social networking increase rapidly.
From Facebook to Twitter, LinkedIn to Flickr – there is a social network for just about anything. As the revolution of social networking continues unabated, there comes a growing need to explore patterns within the networks – a process called social network analysis (SNA) Previously, the world of social network analysis could only be accessed with a bit of computing knowledge. However, an open source programme called Nodexl has changed that by bringing some of the important metrics used to understand a network, and the ability to create impressive network graphs, into Excel.
Nodexl makes understanding a social network graph easy for anyone who can navigate around a spreadsheet. The people that can begin to make use of network graphs range from marketers to activists – and I imagine they are now a staple of any well equipped social media political campaign. There are two basic components of a social graph: What a Tweet Can Tell You. Imagine a tiny little sun, just bursting with heat and light, but trapped inside a hard metal cover with a few holes to let beams of energy stream out from inside.
Now imagine there were millions of those little suns, maybe the size of basketballs or tennis balls, all rolling down an assembly line one after another, each with a unique pattern of holes and beams of light streaming out into the world. That's what Twitter is. Inside every unborn tweet you can find infinite potential - someone will be in a place, with social context and they will say something, anything, and give that potential a form. They will say something and it will be instantly available to anyone in the world who's subscribed. Each tweet has more than 30 fields of metadata under the hood; the value populating each of those fields makes up the unique patterns of holes in the metal cover that lets the light out from inside. "One could spend months mining Twitter using @DataSift," said Paul M. Mapping Online Publics » Blog Archive » Twitter Research Methods.
Social Network Analysis. Social network analysis [SNA] is the mapping and measuring of relationships and flows between people, groups, organizations, computers, URLs, and other connected information/knowledge entities.
The nodes in the network are the people and groups while the links show relationships or flows between the nodes. SNA provides both a visual and a mathematical analysis of human relationships. Management consultants use this methodology with their business clients and call it Organizational Network Analysis [ONA]. ONA allows you to x-ray your organization and reveal the managerial nervous system that connects everything. To understand networks and their participants, we evaluate the location and grouping of actors in the network. We look at a social network -- the "Kite Network" above -- developed by David Krackhardt, a leading researcher in social networks. Degree Centrality Betweenness Centrality Closeness Centrality. NodeXL: Network Overview, Discovery and Exploration for Excel.
Open Tools, Open Data, Open Scholarship for Social Media.