March 17, 2014 Predictive Analytics World – San Francisco: Think Link! Network Insights with No Programming Skills

05MarMay 7, 2015 By Marc Smith

I will present a workshop at Predictive Analytics World in San Francisco on March 17, 2014.

Track 1: Social Media Analysis
Think Link! Network Insights with No Programming Skills

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.

March 5th Talk at Predictive Analytics World 2012 in San Francisco: Crowd Photography for Social Media

04JanMay 7, 2015 By Marc Smith

I will speak this March 4th at the 2012 Predictive Analytics World in San Francisco about ” Crowd Photography for Social Media“.

http://www.predictiveanalyticsworld.com/sanfrancisco/2012/speakers.php
http://www.predictiveanalyticsworld.com/sanfrancisco/2012/agenda.php#

Monday @ 5:25-5:45pm

Track 1:
Social Data Case Study:
Social Media Research Foundation
Crowd Photography for Social Media

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.

Speaker: Marc Smith, Director, Social Media Research Foundation

October 19-20, 2011: NYC – Predictive Analytics World: Network Maps for End Users: Collect, Analyze, Visualize and Communicate Network Insights with Zero Coding

17OctMay 7, 2015 By Marc Smith

I presented on social media network analysis on October 20, 2011 in New York City at Predictive Analytics World.

A map of the connections among the people tweeting about the #Pawcon hashtag is below.

Network Maps for End Users: Collect, Analyze, Visualize and Communicate Network Insights with Zero Coding

Abstract: Networks are everywhere except the end user desktop. NodeXL, the free and open network overview, discovery and exploration add-in for the popular and familiar Excel (2007/2010) spreadsheet allows users who are comfortable making pie charts to now make useful network visualizations. Developed and released by the Social Media Research Foundation, NodeXL uses Excel as a framework, providing a GUI network browser (a “web browser”?) that novices can use quickly and experts can use to generate sophisticated results. Data importers provide access to a range of social media network data sources like Twitter, flickr, YouTube, Facebook, email, the WWW, and more through standard file formats (CSV, GraphML, Matrix). Simple to use tools can automatically analyze, visualize and highlight insights in complex network graphs. Using NodeXL, researchers have been collecting a wide range of network data sets from various social media services. These images reveal a range of common social formations in social media and point to people who occupy strategic locations in these graphs.

This is a map of the connections among the people who tweeted the term “PAWCON” on the first day of the event:

[flickr id=”6261006732″ thumbnail=”medium” overlay=”true” size=”large” group=”” align=”none”]

These are the connections among the Twitter users who recently tweeted the word #pawcon when queried on October 19, 2011, scaled by numbers of followers (with outliers thresholded). Connections created when users reply, mention or follow one another.

A larger version of the image is here: www.flickr.com/photos/marc_smith/6261006732/sizes/l/in/ph…

Top most between users:
@tapan_patel
@pawcon
@sasanalytics
@deloitteba
@kristinevick
@jamet123
@zementis
@kdnuggets
@tibcospotfire
@saspublishing

Graph Metric: Value
Graph Type: Directed
Vertices: 41
Unique Edges: 233
Edges With Duplicates: 120
Total Edges: 353
Self-Loops: 44
Connected Components: 2
Single-Vertex Connected Components: 1
Maximum Vertices in a Connected Component: 40
Maximum Edges in a Connected Component: 352
Maximum Geodesic Distance (Diameter): 4
Average Geodesic Distance: 1.87133
Graph Density: 0.15304878
NodeXL Version: 1.0.1.179

Here is an example map of the connections among the people who tweeted the term “pawcon” in Twitter on September 14th, a week prior to the event.

[flickr id=”6274836259″ thumbnail=”small” overlay=”true” size=”large” group=”” align=”none”] [flickr id=”6274836151″ thumbnail=”small” overlay=”true” size=”large” group=”” align=”none”]

Manu Sharma, Principle Research Scientist at LinkedIn gave a great presentation on the patterns found in their data. Big data, for example, showed that most of the people who previously worked at recently failed banks and financial institutions have updated their profiles to show that they mostly have new jobs at some of the remaining companies in the industry.

The event was held at the New York Hilton: Maps & Directions

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