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.
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.
Networks are everywhere but collecting, analyzing, visualizing, and gaining insights into connected structures can require advanced technical skills. This session presents a free, easy-to-use tool for network analysis that builds on the familiar Excel spreadsheet called NodeXL. If you can make a pie chart, you can get insights into networks. The tool makes it easy to collect data from a range of social media (Twitter, Facebook, YouTube, etc.). Quickly create visualizations and reports on the shape of connected groups. Identify the key people, groups and topics in a community. Network analysis can reveal the hidden structures in streams of interactions.
Hidden within social media streams are structures that identify the most influential voices on any topic. Social network analysis and visualization can take millions of messages and reveal the shape of the crowd and the people at the center of it. Using the free and open NodeXL application, this talk demonstrates the tools and methods needed to create detailed maps of any social media topic. Learn to map and analyze social networks extracted from email, Facebook, Twitter, YouTube, message boards, and the WWW. No coding or prior experience needed!
Workshop: Tuesday, April 16, 2013 From: 6:30pm – 9:30pm
Intended Audience: Social media managers and analysts, marketers, collaboration and enterprise IT, advertisers, event planners, journalists,
Knowledge Level: all skill levels, beginners particularly welcome. Should have an interest in social media. Any experience with a spreadsheet is a plus!
Social media conversations are clumpy. People tend to follow and reply to people who share their views so distinct clusters emerge in many social media discussions. Often these sub-groups have distinct ways of using language, point to different URLs, and mention different hashtags, even when talking about the same topic. Simple, free and open tools can now collect and analyze these clusters of discussion, highlighting the contrasting themes in the conversation. Learn how to perform key tasks like:
Crowds of people gather in social media around many products, services, businesses, and events but they can be difficult to see and understand. With new free and open tools, it is now possible to map and measure social media spaces, capturing the sub-groups and key people within and between them. Learn how to capture social media data and quickly generate a visual map of the crowd. With maps in hand, we will discuss ways they guide a journey to the key influencers and concepts in the crowd.
Here is an updated map of the connections among people who recently tweeted the term “Oracle”:
Connections among the Twitter users who recently tweeted the word Oracle when queried on October 5, 2011, scaled by numbers of followers (with outliers thresholded). Connections created when users reply, mention or follow one another.
Graph Metric: Value
Graph Type: Directed
Unique Edges: 2747
Edges With Duplicates: 827
Total Edges: 3574
Connected Components: 425
Single-Vertex Connected Components: 396
Maximum Vertices in a Connected Component: 541
Maximum Edges in a Connected Component: 2923
Maximum Geodesic Distance (Diameter): 10
Average Geodesic Distance: 3.475208
Graph Density: 0.00226026
NodeXL Version: 22.214.171.124
A related map represents the connections among people who tweeted the term #OOW11
These are the connections among the Twitter users who recently tweeted the word oow11 when queried on October 3, 2011, scaled by numbers of followers (with outliers thresholded). Connections created when users reply, mention or follow one another.
That illustrate the connections among people who tweet the term “#ecomm2010”, scaled by the number of followers.
Abstract: Social network analysis (SNA) is a powerful method for gaining insight into the massive collections of connections created when many people connect to one another through mobile devices. SNA has been widely applied to desktop social media and is moving into the mobile world. Prominent studies of the “call graph” have been produced at national scales.
Mobile providers are applying SNA to identify key subscribers who can reduce churn and help gain adoption of new services and products. Network analysis has historically had a steep learning curve, but now new tools are making SNA easier for less technical users. This talk will describe social network concepts and their application to mobile data sets. A free and open add-in for the popular Excel 2007 spreadsheet called NodeXL (http://www.codeplex.com/nodexl) can perform many complex SNA tasks like data import, scrubbing, metrics calculation, clustering, and visualization. Applying this tool to call graph and subscriber data sets can reveal key positions in the network that can attract and hold other subscribers in the system.