The NodeXL project hit a milestone this week with 250,000 downloads.
Thanks to our users for their continued interest and support of the NodeXL project!
2014
Upcoming 2014 NodeXL Talks, Workshops, and Training
Upcoming talks, workshops and training for social media network analysis and NodeXL.
March 16, 2014: Predictive Analytics World, San Francisco.
Track 1: Social Media Analysis Think Link! Network Insights with No Programming Skills
March 18: Consortium for Service Innovation Annual Member Summit
April 24-24, 2014 The Next Web, Amsterdam
May 1-2, 2014: The Social Media & Web Analytics Summit
May 8th, 2014: 2014 SQL PASS Business Analytics Conference in San Jose.
May 19-23, 2014: International Conference on Collaboration Technologies and Systems, Minneapolis, Minnesota
June 27-29 2014: Networks in the Global World 2014. Bridging Theory and Methods: American, European and Russian Studies
May 19-23, 2014: International Conference on Collaboration Technologies and Systems, Minneapolis, Minnesota
Collaboration, Social Computing, New Media and Networks
(SoMNet 2014)
Call for
Papers and Participation
As part of the
2014 International Conference on Collaboration Technologies and Systems
(CTS 2014)
May 19-23, 2014
The Commons Hotel
Minneapolis, Minnesota, USA
(SoMNet 2014)
Call for
Papers and Participation
As part of the
2014 International Conference on Collaboration Technologies and Systems
(CTS 2014)
May 19-23, 2014
The Commons Hotel
Minneapolis, Minnesota, USA
In Cooperation with
ACM, IEEE, and IFIP
ACM, IEEE, and IFIP
May 7-9, 2014 – SQLPASS – San Jose – Social media network maps in Excel with NodeXL
I will present a talk at the 2014 SQL PASS Business Analytics Conference in San Jose on May 8th.
The talk will focus on free and open tools for creating network maps and reports that can illuminate the landscape of social media.
The graph represents a network of 633 Twitter users whose tweets in the requested date range contained “sqlpass”, or who were replied to or mentioned in those tweets. The tweets in the network were tweeted over the 15-day, 2-hour, 48-minute period from Tuesday, 25 February 2014 at 00:26 UTC to Wednesday, 12 March 2014 at 03:15 UTC.
There is an edge for each “replies-to” relationship in a tweet, an edge for each “mentions” relationship in a tweet, and a self-loop edge for each tweet that is not a “replies-to” or “mentions”.
The graph’s vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm. The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
The edge colors are based on edge weight values. The edge widths are based on edge weight values. The edge opacities are based on edge weight values. The vertex sizes are based on followers values. The vertex opacities are based on followers values.
Top 10 Vertices, Ranked by Betweenness Centrality:
@sqlpass
@laertesqldba
@nikoneugebauer
@karlakay22
@jenstirrup
@retracement
@grrl_geek
@sqlrockstar
@markvsql
@sqlservermag
Top URLs in Tweet in Entire Graph:
http://www.sqlpass.org/ss2014launch/Webinars.aspx
http://www.sqlpass.org/summit/2014/Speakers/CallForSpeakers.aspx
http://sqlsaturday.com/287/schedule.aspx
http://bi.sqlpass.org/
https://attendee.gotowebinar.com/register/5759204879042322946
https://attendee.gotowebinar.com/register/2383471085904007682
http://paper.li/PASSAppDev/1391708680
https://attendee.gotowebinar.com/register/3165768110532010497
https://attendee.gotowebinar.com/register/2196441958679840002
http://www.linkedin.com/slink?code=bNfBsHy
Top Hashtags in Tweet in Entire Graph:
#sqlpass
#sqlserver
#sql
#sqlsatexeter
#sqlpass_de
#sqlsaturday
#sqlsatvienna
#sqlsatportugal
#msbi
#sqlsatmadison
May 1-2, 2014 Talk at Social Media & Web Analytics Summit in San Francisco
I will speak at The Social Media & Web Analytics Summit on May 2nd.
Hosted by The Innovation Enterprise, the event provides 30+ industry case studies and over 20 hours of networking opportunities across 2 days.
The summit will cover the important topics relevant to business today:
- Measuring, Evaluating & Predicting the Social Consumer
- What Consumers Say vs. What They Do
- Multi-Platform Consumer Engagement
- Journey to Social Media ROI
- Multi-Variate Experiments on the Web
- Scientifically Measuring the Wealth of your Website
You can follow the event on Twitter with the hashtag: #IESocialWeb.
#IESocialWeb Twitter NodeXL SNA Map and Report for Friday, 14 March 2014 at 00:30 UTC
April 24-25, 2014: TheNextWeb – Amsterdam – NodeXL talk about mapping social media networks
I spoke at TheNextWeb 2014 in Amsterdam on April 25th.
Here is a map of the connections among the people who recently tweeted the terms: tnwconference OR #TNWEurope OR thenextweb
This is a highly fragmented “Brand” network pattern with several prominent Broadcast hub and spoke structures centered around the most central participants: @thenextweb, @ow, @epro, @nicolasfordham, @gcouros, @malchord, @martinsfp, @plagia3, @k5launch, @taxion2.
I spoke about how anyone who can make a pie chart can now make these network maps and reports.
Interested in a map for a topic important to you? Request a free sample NodeXL social media network map and report.
April 23, 2014 – NodeXL Meetup in Amsterdam
Please join me for a NodeXL meetup on April 23 at 3pm local time in Amsterdam at an event hosted by DTN/NewsConsole.
Location: Prinsengracht 707-3
Bring your SNA, social media, social network, and NodeXL questions along with sample data sets!
Come hear about NodeXL features that make automating network data collection, analysis, visualization and publication simple and easy. Get daily reports on the social networks that matter to you!
I will talk about the upcoming features releasing in NodeXL (autoupdate, new layouts, better importers for Twitter, Facebook, Wikis, and more) and take your requests.
We may have some special guests!
Please RSVP to pascale@dtn.net at DTN.
April 4, 2014 Washington DC NodeXL User Group Meetup at 1776DC
I am happy to announce a Washington, D.C. NodeXL user group meeting.
April 4th, 2014 at 2pm through 5pm (followed by an informal local dinner).
We will be meeting at:
1133 15TH ST. NW
12th floor
Washington, DC 20005
12th floor
Washington, DC 20005
There will be a 3 hour Q&A and hands-on tutorial on the use of NodeXL and broadly on social media network analysis. We will focus on the process of collecting, storing, analyzing, visualizing, and sharing insights into social media network graphs.
Many thanks to Maksim Tsvetovat (@maksim2042) for arranging the location.
Bring your SNA, social media, social network, and NodeXL questions along with sample data sets!
Come hear about NodeXL features that make automating network data collection, analysis, visualization and publication simple and easy. Get daily reports on the social networks that matter to you!
I will talk about the upcoming features releasing in NodeXL (auto update, new layouts, better importers for Twitter, Facebook, Wikis, and more) and take your requests.
If you would like to attend please complete this form:
April 2-4, 2014 Social Computing, Behavioral Modeling and Prediction Conference in Washington D.C.
I will present a tutorial on social media network analysis at the 2014 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP14)
April 2 – April 4, 2014
UCDC Center
Washington DC, USA
The 2014 International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP14) is a multidisciplinary conference with a single paper track and poster session. SBP invites a small number of high quality tutorials and nationally recognized keynote speakers.
The SBP conference provides a forum for researchers and practitioners from academia, industry, and government agencies to exchange ideas on current challenges in social computing, behavioral modeling and prediction, and on state-of-the-art methods and best practices being adopted to tackle these challenges. Interactive events at the conference are designed to promote cross-disciplinary contact.
Social Computing harnesses the power of computational methods to study social behavior within a social context. Behavioral Cultural modeling refers to representing behavior and culture in the abstract, and is a convenient and powerful way to conduct virtual experiments and scenario analysis. Both social computing and behavioral cultural modeling are techniques designed to achieve a better understanding of complex behaviors, patterns, and associated outcomes of interest. Moreover, these approaches are inherently interdisciplinary; subsystems and system components exist at multiple levels of analysis (i.e., “cells to societies”) and across multiple disciplines, from engineering and the computational sciences to the social and health sciences.
April 1, 2014 – NodeXL SNA of social media talk at Federal Big Data Working Group
I will present a talk about social media network at the April 1st Federal Big Data Working Group at 6:30pm.
Talk details are on the SemanticCommunity.info site.
The Federal Big Data Working Group supports the Federal Big Data Initiative and the Federal Digital Government Strategy.
See: http://www.meetup.com/Federal-Big-Data-Working-Group/
The talk will focus on the easy to follow steps needed to create social media network maps and reports automatically from services like Twitter, Facebook, YouTube, Flickr, email, blogs, wikis, and the WWW. Here is a sample network map of the term #bigdataprivacy:
The graph represents a network of 248 Twitter users whose recent tweets contained “#bigdataprivacy”, or who were replied to or mentioned in those tweets. The tweets in the network were tweeted over the 6-day, 10-hour, 29-minute period from Tuesday, 25 February 2014 at 14:36 UTC to Tuesday, 04 March 2014 at 01:06 UTC. 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 graph’s vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.
The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
The edge colors are based on edge weight values. The edge widths are based on edge weight values. The edge opacities are based on edge weight values. The vertex sizes are based on followers values. The vertex opacities are based on followers values.
Top 10 Vertices, Ranked by Betweenness Centrality:
@whitehouseostp, @mit, @mit_csail, @steve_lockstep, @aureliepols, @dbarthjones, @digiphile, @stannenb, @djweitzner, @mikaelf
Top URLs in Tweet in Entire Graph:
http://web.mit.edu/bigdata-priv/webcast.html
http://www.commerce.gov/news/secretary-speeches/2014/03/03/us-secretary-commerce-penny-pritzker-delivers-remarks-mit
http://web.mit.edu/bigdata-priv/agenda.html
http://www.whitehouse.gov/blog/2014/02/24/privacy-workshop-explore-big-data-opportunities-challenges
http://www.nytimes.com/glogin?mobile=1&URI=http%3A%2F%2Fmobile.nytimes.com%2F2014%2F03%2F03%2Ftechnology%2Fwhen-start-ups-dont-lock-the-doors.html
http://www.techrepublic.com/article/privacy-concerns-about-data-collection-may-lead-to-dumbing-down-smart-devices/
http://m.technologyreview.com/news/525131/intel-designs-a-safe-meeting-place-for-private-data/
http://thedatamap.org
http://www.foreignaffairs.com/articles/140741/craig-mundie/privacy-pragmatism
http://www.cs.ucdavis.edu/~franklin/ecs289/2010/dwork_2008.pdf