NodeXL has new updates to its importers for Twitter users and lists.
We have released an updated version of NodeXL that simplifies and merges the previously separate User and List importers.
The new, streamlined importer treats an individual user as a list of one.
Lists can be defined by pointing to an existing Twitter List or simply entering a list of delimited user names into the text box.
The updated importer now collects many more tweets per person and parses these messages to generate reply and mention edges.
You can now define a group of Twitter users and find out how much they reply and mention one another.
You can even pull in the followers of each person, to see if they reply or mention people they also follow.
But ever since June 11, 2013, Twitter has made access to the “follows” edge data very difficult (its just very slow). Designed and implemented prior to the update that restricted access to the follower network, the original NodeXL Twitter list importers relied mostly on queries that are now impractically slow for all but the smallest lists of users who have small collections of followers.
The update to these User and List importer is partially an adaptation to these changes. The importer shifts away from the follower network to focus on the communication interaction data in the content of Tweets. Since Twitter offers more generous access to Tweets than to information about who follows who, we are obliged to make better use of what they do offer.
The results are insightful! Here is a map of the connections among the members of the United States Congress.
I am delighted to be attending and presenting a workshop on social media network analysis at the University of Kentucky’s LINKS 2013 program on June 7th, 2013.
This week long program has for many years provided intensive training in network methods, research, and tools.
I am excited to attend some of the program and meet researchers and students working on networks of all sorts. I will do a short hands-on talk about NodeXL and a longer day devoted to the broader ways networks are useful for the study of social media.
Here is a recent collection of NodeXL related activity and commentary:
Here is a great review of Analyzing social media networks with NodeXL: Insights from a connected world by Gerd Waloszek, SAP User Experience book reviewer:
Several reviews of the book Analyzing Social Media Networks with NodeXL: Insights from a connected world have appeared on the Amazon page:
Here is the blog review of Analyzing social media networks with NodeXL: Insights from a connected world that is the source of the second review:
The book has now entered the used market: you can find it on eBay, oddly at the same price as Amazon sells it new!
Great video demo of Cytoscape Venn and Euler diagrams of network graphs:
Even better, a video Demo of MSR work on Euler diagrams:
Review of recent NodeXL demo at the Social Tech 2010 conference.
NodeXL mentioned in a blog:
AT&T Research blog post on the value of network visualizations:
You should really watch this video: it is the future! If you watch it, you will get +10 points!
Translated from Czech: Identification of communities around the Twitter account
Animators of Life – Why information visualization matters! Network visualization is even harder! > 3D Worth a look.
NodeXL used to map Conan O’Brien (US TV Talk Show Host)
“Using NodeXL to collect the data and Gephi to visualize the networks of the Youtube videos mentioning “teamcoco” and collecting the tweets containing hashtag #conanreturns.”
Have a look at LateralData’s Relationship analyzer:
My colleague at the Oxford Internet Institute, Bernie Hogan, is working on tools that collect personal Facebook network data and visualize the connections among your friends. These tools now interoperate with NodeXL through the GraphML XML file format. Here is the new link: http://namegen.oii.ox.ac.uk/fb/downloadNet.php?type=graphml
Here is an example: http://twitpic.com/9rvfq
It provides a good illustration of the ways a person’s social network is clumped into clusters built around life phases, workplaces, educational institutions, teams and locations. As people move through more of these stages of life during the Facebook era (and often before) they accumulate these clusters.
Facebook or other contact and friend management systems might could leverage this clustering to organize the presentation of contact information streams.
Bernie recently announced on the SOCNET list that he has updated his script for downloading your Facebook network.
1. Its faster. (Presently orders of magnitude faster than Nexus, Touchgraph or ORA).
2. It gives nice feedback during the download.
3. It has less bugs!
4. It gives you the output as a file you can right-click and save rather than copy-paste.
5. IDs are names.”
Bernie writes that phase two of his project is underway.
Bernie is planning a demo at the Sunbelt social network analysis conference in Italy in 2010.
Bernie is the author of the Facebook chapter in our forthcoming book Analyzing Social Media Networks with NodeXL: Insights from a connected world available from Morgan-Kaufmann in July 2010.