Hello North Bay Area network analysis fans!
Join the NodeXL users meetup at the Napa Embassy Suites hotel (1075 California Boulevard, Napa, California, 94559, USA) on the 27th of February at 6pm.
Meet other network, social network, and social media network researchers and practitioners.
Hear about the latest and upcoming updates in the free and open NodeXL application.
Connect to the NodeXL network! Please RSVP using the form below:
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There will be a one day crash course on all things “big data” at the upcoming San Francisco Predictive Analytics World conference on Monday, March 30th, 2015. Get the Big Data big picture with a day of introduction to the major concepts, methods, challenges, and best practices related to leveraging large volumes of information.
There will be a session on social media network analysis using NodeXL at the conference as well.
http://www.predictiveanalyticsworld.com/sanfrancisco/2015/agenda.php#day1-1120b
11:20am-12:05pm
Track 2: Social Data
Think Link: Connecting to the Power of Social Networks with no Programing with NodeXL
Networks are collections of connections — they are everywhere once you start to look. Learn how to collect, analyze, visualize, and publish insights into connected populations. Using the free and open NodeXL addin for Excel, anyone who can make a pie chart can now make a network chart. Create insights into social media, collaboration, organizations, markets, and other connected structures with just a few clicks. Easily publish reports with visualizations and content analysis. Apply social network analysis to your own brands, email, discussions or web sites.
I participated in a webinar hosted by the Prospect Research Institute. We discussed the ways that NodeXL can simplify the task of collecting social media and social network data. The tool generates easy to understand reports that highlight insights into connected structures.
The slides associated with the talk can be found here:
Analyzing Social Media Networks with NodeXL: Insights from a Connected World
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.
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
