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Here is a map of connections among people who recently tweeted the term “peoplebrowsr”.
“But what does that picture mean?”
I hear this reaction frequently when I show people maps I have made of social media connections.
I often point out that the map and the data can reveal people who occupy important locations in the network as well as emergent clusters and groups.
“So why didn’t you just say so?”
I hear this reaction frequently when I explain what is important about a network.
In NodeXL version 203 we have released a new feature called Graph Summary. Our goal is to “just say so”.
In this version we introduce the basics of automatic captioning. In the NodeXL>Graph menu we now have a “Summary” button:
NodeXL will collect information about the creation and configuration of the network. The dialog box looks like this:
Note that NodeXL>Data>Save Import Details in Graph Summary must be selected in the Import menu for the “Data Import” field to be populated.
Selecting “Copy to Clipboard” will load a copy of these text fields into the buffer. An example of that caption is here:
The graph represents a network of up to 1000 Twitter users whose recent tweets contained "peoplebrowsr". The network was obtained on Friday, 09 March 2012 at 01:21 UTC. There is an edge for each follows relationship. There is an edge for each "replies-to" relationship in a tweet. There is an edge for each "mentions" relationship in a tweet. There is a self-loop edge for each tweet that is not a "replies-to" or "mentions". The earliest tweet in the network was tweeted on Friday, 02 March 2012 at 02:39 UTC. The latest tweet in the network was tweeted on Friday, 09 March 2012 at 00:47 UTC. The graph is directed. The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm. The edge colors are based on relationship values. The vertex sizes are based on followers values. Overall Graph Metrics: Vertices: 74 Unique Edges: 172 Edges With Duplicates: 123 Total Edges: 295 Self-Loops: 42 Connected Components: 15 Single-Vertex Connected Components: 13 Maximum Vertices in a Connected Component: 58 Maximum Edges in a Connected Component: 276 Maximum Geodesic Distance (Diameter): 4 Average Geodesic Distance: 2.014176 Graph Density: 0.036653091447612 Modularity: 0.288302 Top 10 Vertices, Ranked by Betweenness Centrality: @peoplebrowsr @andrewgrill @traviswallis @thenickfrost @jas @alexbudge @getmingly @milener @jeffreyhayzlett @johnnosta The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm. More NodeXL network visualizations are here: www.flickr.com/photos/marc_smith/sets/72157622437066929/ and here: www.nodexlgraphgallery.org/Pages/Default.aspx A gallery of NodeXL network data sets is available here: nodexlgraphgallery.org/Pages/Default.aspx?search=twitter NodeXL is free and open and available from www.codeplex.com/nodexl NodeXL is developed by the Social Media Research Foundation (www.smrfoundation.org) - which is dedicated to open tools, open data, and open scholarship. Donations to support NodeXL are welcome through PayPal: https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=J5AERGAAN552S The book, Analyzing social media networks with NodeXL: Insights from a connected world, is available from Morgan Kaufmann and from Amazon. http://www.amazon.com/gp/product/0123822297?ie=utf8&tag=conneactio-20&linkcode=as2&camp=1789&creative=390957&creativeasin=0123822297
This caption will expand in our next several releases to include information about the top URLs, hashtags, and @usernames in text fields associated with nodes and edges. Following that we will release a series of features to allow for the extraction of keyword pairs in those text fields (our current version of this feature is described here: Keyword Networks: create word association networks from text with NodeXL (with a macro)).