Every network visualization should have a legend that explains what the colors, edge widths, and filters are that define the network graph.
NodeXL automatically generates a network legend and displays it when the Graph Elements menu is opened:
And the “Legend” option is selected.
This will place a legend at the bottom of the visualization canvas:
NodeXL allows users to gather vertices into named collections called “Groups”. This is handy whenever the entities in the network are made up of different types or an algorithm has divided the network into sub-regions based on how densely some vertices connect to one another. The Groups menu is found in the NodeXL>Analysis menu:
Since version v.132 of NodeXL it has been possible to Collapse a group of vertices (See: Expand and Collapse Groups of Vertices with NodeXL v.132). When a group is collapsed all of the vertices within that group are removed from the network graph and replaced with a single vertex with a size proportionate to the number of vertices in the group. A small “+” plus sign indicates that the vertex is a placeholder for a group of vertices.
If the user expands a collapsed group all of the vertices that had been hidden return to positions in the network visualization. The Groups menu has commands for creating, collapsing, and expanding groups.
NodeXL (v.166) now has the ability to automatically collapse or expand any group of vertices conditionally based on any attribute in the workbook using the Autofill Columns feature.
The NodeXL Autofill columns feature allows users to map data elements to display elements. At the bottom of this list (you may need to scroll down to see it) you will now find a new row: Group Collapsed?
There are several network metric attributes for each group that are created when the Find Groups and then the Graph Metrics command has been run on a network in NodeXL:
Selecting one of the data items in the drop down allows you to automatically decide if a group with those attributes will be presented in a collapsed or (default) expanded state. The data about each group include the number of vertices within the group, the number of connections between those vertices, the number of non-unique connections, the number of unique connections among the vertices, the number of self-connections, the number of unique connected components, the number of isolated vertices, the number of vertices in the largest component, the number of edges in the largest component, the maximum and average width of the largest component, and the density of the group.
These metrics allow for the automated processing of the graph to measure each group and apply a test to decide if a group is too dense or populous to be seen in an expanded state.
Recently, we’ve been setting out to set up a new way to set the option settings in NodeXL. Now we have added a new feature to NodeXL (v.166): savable, selectable configuration option settings files.
This may seem dull but this feature may have a big impact on the ease of use of NodeXL. This may let the most experienced users of NodeXL share their best practices with the rest of the user community.
Throughout NodeXL you can set a wide range of values, options, and settings. Change the default size of a font in the Graph Options and we record that setting. Map the size of a vertex to a value associated with it in Autofill columns and we record the setting.
Until now, we recorded the settings in several places: some settings went with each workbook, some settings were associated with each machine and stayed on each desktop. The result was that I could create a great network visualization, save and send someone the workbook and they often would not see what I saw when they opened and visualized the network graph. Why? People set their settings in lots of different ways, on different machines, creating potentially vastly different results.
Now, NodeXL will record everything about how a network workbook should be rendered in that workbook.
This now also means that expert users can save their settings for NodeXL and exchange them with other users.
NodeXL now has three places to put settings that should make it more reliable to share a workbook and get the same results on different systems. There will now be a default NodeXL settings file, a per NodeXL workbook settings file (stored in a hidden worksheet in the workbook) and any number of saved settings files. Users can save their settings in each workbook or decide to save the workbook’s custom set of settings to overwrite the default settings file that will be applied to all subsequent NodeXL workbooks. Users can also save their settings to one or more named files, which can be shared with others. Users can import any of these settings files and apply them to an open workbook by selecting NodeXL>Options>Import.
For those who are running automated collections that then run automated processing of a workbook (see: How to schedule the creation of a network with NodeXL and Windows Task Scheduler) you should note that:
NodeXL now (v.166) offers users a set of keyboard shortcuts that can speed up your routine network layout tasks.
After you click in the graph pane, a number of keyboard shortcuts are now available for functions that had previously been available in the visualization pane’s right-click menu. Now, you can press:
Ctrl+A to select all vertices and edges
Ctrl+V to select all vertices
Ctrl+E to select all edges
Ctrl+D to deselect everything
Ctrl+P to edit the properties of the selected vertices
Ctrl+C to save the graph image to the Windows clipboard
Ctrl+I to save the graph image to a file
Arrow key to move the selected vertices a small distance
Shift+arrow key to move the selected vertices a large distance.
(If you forget a shortcut, most of them are listed in the graph pane’s right-click menu.)
If you have any suggestions for other frequent tasks that could be accelerated with a keyboard command, please contact us on the NodeXL discussion board or here in the comments.
I will present a workshop on social media network analysis at the next Network Singularity event at Fort Mason on the Bay in San Francisco on April 30, 2010.
Bay Area and Silicon Valley Network: Special Action/Research Event
Social Media Network Analysis: Next Practices in Social Network Analysis, Tools and Media
Friday 30 April 2010
8:00am -5:00pm
http://www.regonline.com/BAN10
Workshop Abstract
Why do some social media and online groups succeed when others fail? How do different collections of online media and populations of authors and users differ from one another? How do patterns of contribution vary? How do these differences illustrate the roles people play within their communities?
Patterns of contribution and connection determines social media success. Visualizing these network patterns aids implementation, adoption, security and effectiveness of social media. A range of Internet social media including discussion groups, Twitter, enterprise social media, communities-of-practice, blogs and email are presented, analyzed and visualized. Network patterns are explored to illustrate the scope of variation among social media repositories and between types of contributors.
Maps and patterns of interaction deliver a far more comprehensive view of social media. These views generate actionable findings to improve social media effectiveness, syndication and collaborative outcomes. Network analysis and intelligence can guide community cultivation, coordination and development tasks. New network capabilities provision features that improve search, ranking and consumption of user generated content.
A freely available, open source tool will be demonstrated to perform basic social media network analysis for contemporary social media that should be relevant to business models and organizations of all types. Delegates will be equipped to use social network techniques to improve overall effectiveness and impact of social media, communities-of-practice and social software applications. Participants may expect to achieve immediate improvements in key business activities such as marketing, sales, engineering, support, service, innovation and overall organizational effectiveness.
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The eruption of Eyjafjallajokull in Iceland has created disruption of air traffic around the world and particularly through Northern Europe. A similar eruption of tweets has followed, focused around a series of hastags including “#ashtag”, “#ashcloud”, and “#volcano”.
The #ashtag network is highlighted by well known technology bloggers.
In contrast the map for the tag “#ashcloud” is dominated by the UK and Scottish travel and Foreign office twitter accounts.
This image features a minor but useful tip for building multi-line tooltips. This can help pack a lot of information about a Node into the tooltip. To build a multi-line tooltip use the “&CHAR(10)&” feature to glue other columns of data together along with labels.
Add a column to the Vertices worksheet and paste something like this into it:
=”Twitter user: “&Vertices[[#This Row],[Vertex]]&” – Followers:”&Vertices[[#This Row],[Followers]]&CHAR(10)&”Description: “&Vertices[[#This Row],[Description]]&CHAR(10)&”Last tweet: “&Vertices[[#This Row],[Tweet]]
Which creates a tooltip with multiple lines containing the Twitter User name, the number of their followers, a new line containing their user description followed by their last tweet on another line. Any concatenation of columns contents can be assembled in this way.
The Twitter Chirp conference attracted tweets from many technology leaders and bloggers. Here is a ranked list of the top most “between” people who tweeted the term “chirp” in the last day.
A complete social network map, with edge thickness proportional to the number of network connections (follows, replies, mentions) that link the two participants is here:
The zoomed version highlights the key players in the network and the tighter connections that surround the account for Twitter founder “Ev”.
The CHI 2010 conference is well underway in Atlanta this week and lots of people are tweeting the #CHI2010 hash tag. An updated NodeXL map of the connections among people who use the #CHI2010 tag is below:
This is the network map of follows, replies, and mentions relationships among Twitter users who mentioned “CHI2010” as of April 12, 2010 scaled by number of followers.
This chart is a log/linear plot of followers (X) over tweets (Y).
Some people tweet a lot in order to get lots of followers, while others can tweet only modestly and gain a vast following. On a log/log scale this looks like:
The log scales are mislabeled (it is a known, pending work item!), but the pattern is clear: Tweet more and get more Followers. Some people break from the pack, of course, leading or lagging the core population. The tooltip is the latest tweet from the most followed Twitter author in the population.
The right click menu is a source of many good things in NodeXL. In the graph pane, the right click menu contains several options of possible interest.
This is a map of the recent connections among twitter users who tweeted the string “NodeXL”. Each profile photo is scaled to the number of followers that person has. In this image one author node is right-clicked and reveals some useful options. Highlighted in the image is the option to open the twitter page for this person. Also of use is the Edit Selected Vertex Properties option where nodes can have their labels moved around (top, bottom, left, etc) and switched on and off in the graph.
Right-click features appear elsewhere in the application. It is worth poking at things with the right-click menu but we will be working on surfacing these options more clearing in forthcoming releases.
You can add your own right-click menus to your own networks by using the custom vertex menu option. Find out how after the jump.
