Table of contents
  1. Story
    1. NodeXL Twitter Social Network Map for the #datacommunitydc
  2. Story
    1. NodeXL Twitter Social Network Map for the #bigdataprivacy
  3. Slides
    1. NodeXL
      1. GraphML File Processor
      2. GraphML File Processor Message
      3. NodeXL Interface
      4. Help
      5. Slide 1 Charting Collections of Connections in Social Media with NodeXL
      6. Slide 2 About Me
      7. Slide 3 Social Media Research Foundation Map
      8. Slide 15 Social Networks
      9. Slide 17 Social Media Research Foundation
      10. Slide 18 Introduction to NodeXL
      11. Slide 19 Network Analysis Data Flow
      12. Slide 29 NodeXL Graph Gallery
      13. Slide 30 Social Network Maps Reveal
      14. Slide 37 NodeXL Add-in for Excel 2007/2010
      15. Slide 39 Six Kinds of Twitter Social Media Networks
      16. Slide 47 Social Network Theory
      17. Slide 48 SNA 101
      18. Slide 49 NodeXL Senate Data Example
      19. Slide 51 Goal: Make SNA Easier
      20. Slide 55 NodeXL Graph Gallery
      21. Slide 56 Book Now Available
      22. Slide 62 NodeXL Calculates Network Metrics and Word Pairs
      23. Slide 70 NodeXL Data Import Sources
      24. Slide 82 Social Media Research Foundation Matrix
      25. Slide 83 What We Are Trying To Do
      26. Slide 88 What We Want To Do
    2. Sci2 Tool
  4. Spotfire Dashboard
  5. Research Notes
    1. NodeXL
    2. Sci2 Tool
  6. NodeXL: Network Overview, Discovery and Exploration for Excel
    1. NodeXL Features
    2. NodeXL for Programmers
    3. NodeXL is Brought to You By...
    4. Contributors to NodeXL
    5. Getting Started
  7. NodeXL: Network Overview, Discovery and Exploration in Excel
    1. The tool includes an Excel template for easy manipulation of graph data
    2. NodeXL includes a number of features, summarized in the NodeXL Chart:
    3. Research Overview
    4. Sample networks generated with NodeXL
    5. Project contributors
    6. Clustered Graph using Harel-Koren layout in NodeXL
    7. NodeXL 'Group-in-a-box' Layout of the Clustered graph
  8. Other
    1. Microsoft Research Collaborators
    2. External Collaborators
    3. Related Links
  9. Analyzing Social Media Networks with NodeXL: Insights from a Connected World
    1. Chapter 3 Social Network Analysis Measuring, Mapping, and Modeling Collections of Connections
    2. Chapter 4 Getting Started with NodeXL, Layout, Visual Design, and Labeling
    3. Chapter 5 Calculating and Visualizing Network Metrics
    4. Chapter 6 Preparing Data and Filtering
    5. Chapter 7 Clustering and Grouping
    6. Chapter 8 Email: The Lifeblood of Modern Communication
    7. Chapter 9 Thread Networks Mapping Message Boards and Email Lists
    8. Chapter 10 Twitter Conversation, Entertainment, and Information, All in One Network!
    9. Chapter 11 Visualizing and Interpreting Facebook Networks
    10. Chapter 12 WWW Hyperlink Networks
    11. Chapter 13 Flickr Linking People, Photos, and Tags
    12. Chapter 14 YouTube Contrasting Patterns of Content, Interaction, and Prominence
    13. Chapter 15 Wiki Networks Connections of Creativity and Collaboration
  10. IT 101 Lab: Analyzing Your Facebook or Twitter Network
    1. Purpose
    2. Procedures
      1. Step 1. Install NodeXL and importers
      2. Step 2. Use NodeXL to import the data you want to analyze 1
      3. Step 3. Create metrics and calculate clusters
      4. Step 4a. Visualize Your Network
      5. Step 4b. Fine-Tune Your Visualization
      6. Step 5. Create Your Final Visualization and Write-up
    3. ​​Reference
      1. 1
  11. NodeXL Help
    1. An Overview of Network Graphs
    2. A Quick Tour of the NodeXL Workbook
      1. The NodeXL Worksheets
      2. The Graph Pane
        1. The Graph Pane
        2. The Graph Legend
        3. The Graph Axes
      3. The NodeXL Ribbon Tab
    3. Creating a Simple Graph
    4. Directed vs. Undirected Graphs
    5. Graphs with Isolated Vertices
    6. Zooming, Moving Around and Scaling the Graph
      1. Zooming the Graph
      2. Moving Around the Graph
      3. Scaling the Graph
    7. Selecting Graph Elements
      1. Selecting Vertices
      2. Selecting Edges
    8. Changing How the Graph Looks
      1. Default Visual Properties: Graph Options
      2. Setting Visual Properties for Individual Edges, Vertices or Groups
      3. Automatically Calculating Visual Properties for All Edges, Vertices or Groups
      4. Labeling Edges, Vertices and Groups
    9. Changing How the Graph is Laid Out
      1. Layout Algorithms
      2. Selectively Laying Out Parts of the Graph Again
      3. Snapping Vertices to a Grid
      4. Layout Options
    10. Adding Tooltips to the Graph
    11. Saving an Image of the Graph
    12. Analyzing the Graph
      1. Calculating Graph Metrics
      2. Creating Subgraph Images
      3. Using Dynamic Filters
    13. Working with Options
      1. Using the Current Workbook's Options for New Workbooks
      2. Exporting and Importing Options
      3. Resetting All Options
    14. Working with Groups
      1. Creating Groups
        1. Creating Groups by Vertex Attribute
        2. Creating Groups by Connected Component
        3. Creating Groups by Cluster
        4. Creating Groups by Motif
        5. Manually Creating Groups
      2. Understanding the Group Worksheets
      3. How Groups Are Shown in the Graph Pane
        1. Color and Shape
        2. Group Layout
        3. Skipping All Groups
        4. Changing How Vertex Colors and Shapes are Specified
      4. Selecting Groups
      5. Collapsing and Expanding Groups
      6. Hiding and Skipping Groups
      7. Removing Groups
      8. Showing and Hiding Workbook Columns
      9. Showing and Hiding Graph Elements
      10. Summarizing the Graph
    15. Importing Graph Data
      1. Importing Graph Data from Other Programs
      2. Importing Graph Data from Another Workbook
      3. Importing Graph Data from Email
      4. Importing Graph Data from Online Social Networks
    16. Exporting Graph Data
      1. Exporting Graph Data to Other Programs
      2. Exporting Graph Data to Another Workbook
    17. Counting and Merging Duplicate Edges
    18. Automating Common Tasks
    19. Keyboard Shortcuts in the Graph Pane
    20. The NodeXL Network Server
    21. Where to Go for More Information
  12. Sci2 Tool
    1. A Tool for Science of Science Research & Practice
    2. News
    3. Please cite as
    4. Sci2 Help
    5. Acknowledgements
    6. Download
    7. Release Notes
    8. Supplemental Plugins
    9. SHOW ARCHIVED VERSIONS
    10. FAQ
    11. Sci2 Help
    12. Documentation
      1. User Manual and Handouts
      2. Classroom Usage
      3. Tutorials
      4. Publications
      5. Download Plugins from Other Tools
    13. Testimonials
    14. Scientific Publications that Use Sci2
  13. NEXT

NodeXL and Sci2 for Data Science

Last modified
Table of contents
  1. Story
    1. NodeXL Twitter Social Network Map for the #datacommunitydc
  2. Story
    1. NodeXL Twitter Social Network Map for the #bigdataprivacy
  3. Slides
    1. NodeXL
      1. GraphML File Processor
      2. GraphML File Processor Message
      3. NodeXL Interface
      4. Help
      5. Slide 1 Charting Collections of Connections in Social Media with NodeXL
      6. Slide 2 About Me
      7. Slide 3 Social Media Research Foundation Map
      8. Slide 15 Social Networks
      9. Slide 17 Social Media Research Foundation
      10. Slide 18 Introduction to NodeXL
      11. Slide 19 Network Analysis Data Flow
      12. Slide 29 NodeXL Graph Gallery
      13. Slide 30 Social Network Maps Reveal
      14. Slide 37 NodeXL Add-in for Excel 2007/2010
      15. Slide 39 Six Kinds of Twitter Social Media Networks
      16. Slide 47 Social Network Theory
      17. Slide 48 SNA 101
      18. Slide 49 NodeXL Senate Data Example
      19. Slide 51 Goal: Make SNA Easier
      20. Slide 55 NodeXL Graph Gallery
      21. Slide 56 Book Now Available
      22. Slide 62 NodeXL Calculates Network Metrics and Word Pairs
      23. Slide 70 NodeXL Data Import Sources
      24. Slide 82 Social Media Research Foundation Matrix
      25. Slide 83 What We Are Trying To Do
      26. Slide 88 What We Want To Do
    2. Sci2 Tool
  4. Spotfire Dashboard
  5. Research Notes
    1. NodeXL
    2. Sci2 Tool
  6. NodeXL: Network Overview, Discovery and Exploration for Excel
    1. NodeXL Features
    2. NodeXL for Programmers
    3. NodeXL is Brought to You By...
    4. Contributors to NodeXL
    5. Getting Started
  7. NodeXL: Network Overview, Discovery and Exploration in Excel
    1. The tool includes an Excel template for easy manipulation of graph data
    2. NodeXL includes a number of features, summarized in the NodeXL Chart:
    3. Research Overview
    4. Sample networks generated with NodeXL
    5. Project contributors
    6. Clustered Graph using Harel-Koren layout in NodeXL
    7. NodeXL 'Group-in-a-box' Layout of the Clustered graph
  8. Other
    1. Microsoft Research Collaborators
    2. External Collaborators
    3. Related Links
  9. Analyzing Social Media Networks with NodeXL: Insights from a Connected World
    1. Chapter 3 Social Network Analysis Measuring, Mapping, and Modeling Collections of Connections
    2. Chapter 4 Getting Started with NodeXL, Layout, Visual Design, and Labeling
    3. Chapter 5 Calculating and Visualizing Network Metrics
    4. Chapter 6 Preparing Data and Filtering
    5. Chapter 7 Clustering and Grouping
    6. Chapter 8 Email: The Lifeblood of Modern Communication
    7. Chapter 9 Thread Networks Mapping Message Boards and Email Lists
    8. Chapter 10 Twitter Conversation, Entertainment, and Information, All in One Network!
    9. Chapter 11 Visualizing and Interpreting Facebook Networks
    10. Chapter 12 WWW Hyperlink Networks
    11. Chapter 13 Flickr Linking People, Photos, and Tags
    12. Chapter 14 YouTube Contrasting Patterns of Content, Interaction, and Prominence
    13. Chapter 15 Wiki Networks Connections of Creativity and Collaboration
  10. IT 101 Lab: Analyzing Your Facebook or Twitter Network
    1. Purpose
    2. Procedures
      1. Step 1. Install NodeXL and importers
      2. Step 2. Use NodeXL to import the data you want to analyze 1
      3. Step 3. Create metrics and calculate clusters
      4. Step 4a. Visualize Your Network
      5. Step 4b. Fine-Tune Your Visualization
      6. Step 5. Create Your Final Visualization and Write-up
    3. ​​Reference
      1. 1
  11. NodeXL Help
    1. An Overview of Network Graphs
    2. A Quick Tour of the NodeXL Workbook
      1. The NodeXL Worksheets
      2. The Graph Pane
        1. The Graph Pane
        2. The Graph Legend
        3. The Graph Axes
      3. The NodeXL Ribbon Tab
    3. Creating a Simple Graph
    4. Directed vs. Undirected Graphs
    5. Graphs with Isolated Vertices
    6. Zooming, Moving Around and Scaling the Graph
      1. Zooming the Graph
      2. Moving Around the Graph
      3. Scaling the Graph
    7. Selecting Graph Elements
      1. Selecting Vertices
      2. Selecting Edges
    8. Changing How the Graph Looks
      1. Default Visual Properties: Graph Options
      2. Setting Visual Properties for Individual Edges, Vertices or Groups
      3. Automatically Calculating Visual Properties for All Edges, Vertices or Groups
      4. Labeling Edges, Vertices and Groups
    9. Changing How the Graph is Laid Out
      1. Layout Algorithms
      2. Selectively Laying Out Parts of the Graph Again
      3. Snapping Vertices to a Grid
      4. Layout Options
    10. Adding Tooltips to the Graph
    11. Saving an Image of the Graph
    12. Analyzing the Graph
      1. Calculating Graph Metrics
      2. Creating Subgraph Images
      3. Using Dynamic Filters
    13. Working with Options
      1. Using the Current Workbook's Options for New Workbooks
      2. Exporting and Importing Options
      3. Resetting All Options
    14. Working with Groups
      1. Creating Groups
        1. Creating Groups by Vertex Attribute
        2. Creating Groups by Connected Component
        3. Creating Groups by Cluster
        4. Creating Groups by Motif
        5. Manually Creating Groups
      2. Understanding the Group Worksheets
      3. How Groups Are Shown in the Graph Pane
        1. Color and Shape
        2. Group Layout
        3. Skipping All Groups
        4. Changing How Vertex Colors and Shapes are Specified
      4. Selecting Groups
      5. Collapsing and Expanding Groups
      6. Hiding and Skipping Groups
      7. Removing Groups
      8. Showing and Hiding Workbook Columns
      9. Showing and Hiding Graph Elements
      10. Summarizing the Graph
    15. Importing Graph Data
      1. Importing Graph Data from Other Programs
      2. Importing Graph Data from Another Workbook
      3. Importing Graph Data from Email
      4. Importing Graph Data from Online Social Networks
    16. Exporting Graph Data
      1. Exporting Graph Data to Other Programs
      2. Exporting Graph Data to Another Workbook
    17. Counting and Merging Duplicate Edges
    18. Automating Common Tasks
    19. Keyboard Shortcuts in the Graph Pane
    20. The NodeXL Network Server
    21. Where to Go for More Information
  12. Sci2 Tool
    1. A Tool for Science of Science Research & Practice
    2. News
    3. Please cite as
    4. Sci2 Help
    5. Acknowledgements
    6. Download
    7. Release Notes
    8. Supplemental Plugins
    9. SHOW ARCHIVED VERSIONS
    10. FAQ
    11. Sci2 Help
    12. Documentation
      1. User Manual and Handouts
      2. Classroom Usage
      3. Tutorials
      4. Publications
      5. Download Plugins from Other Tools
    13. Testimonials
    14. Scientific Publications that Use Sci2
  13. NEXT

  1. Story
    1. NodeXL Twitter Social Network Map for the #datacommunitydc
  2. Story
    1. NodeXL Twitter Social Network Map for the #bigdataprivacy
  3. Slides
    1. NodeXL
      1. GraphML File Processor
      2. GraphML File Processor Message
      3. NodeXL Interface
      4. Help
      5. Slide 1 Charting Collections of Connections in Social Media with NodeXL
      6. Slide 2 About Me
      7. Slide 3 Social Media Research Foundation Map
      8. Slide 15 Social Networks
      9. Slide 17 Social Media Research Foundation
      10. Slide 18 Introduction to NodeXL
      11. Slide 19 Network Analysis Data Flow
      12. Slide 29 NodeXL Graph Gallery
      13. Slide 30 Social Network Maps Reveal
      14. Slide 37 NodeXL Add-in for Excel 2007/2010
      15. Slide 39 Six Kinds of Twitter Social Media Networks
      16. Slide 47 Social Network Theory
      17. Slide 48 SNA 101
      18. Slide 49 NodeXL Senate Data Example
      19. Slide 51 Goal: Make SNA Easier
      20. Slide 55 NodeXL Graph Gallery
      21. Slide 56 Book Now Available
      22. Slide 62 NodeXL Calculates Network Metrics and Word Pairs
      23. Slide 70 NodeXL Data Import Sources
      24. Slide 82 Social Media Research Foundation Matrix
      25. Slide 83 What We Are Trying To Do
      26. Slide 88 What We Want To Do
    2. Sci2 Tool
  4. Spotfire Dashboard
  5. Research Notes
    1. NodeXL
    2. Sci2 Tool
  6. NodeXL: Network Overview, Discovery and Exploration for Excel
    1. NodeXL Features
    2. NodeXL for Programmers
    3. NodeXL is Brought to You By...
    4. Contributors to NodeXL
    5. Getting Started
  7. NodeXL: Network Overview, Discovery and Exploration in Excel
    1. The tool includes an Excel template for easy manipulation of graph data
    2. NodeXL includes a number of features, summarized in the NodeXL Chart:
    3. Research Overview
    4. Sample networks generated with NodeXL
    5. Project contributors
    6. Clustered Graph using Harel-Koren layout in NodeXL
    7. NodeXL 'Group-in-a-box' Layout of the Clustered graph
  8. Other
    1. Microsoft Research Collaborators
    2. External Collaborators
    3. Related Links
  9. Analyzing Social Media Networks with NodeXL: Insights from a Connected World
    1. Chapter 3 Social Network Analysis Measuring, Mapping, and Modeling Collections of Connections
    2. Chapter 4 Getting Started with NodeXL, Layout, Visual Design, and Labeling
    3. Chapter 5 Calculating and Visualizing Network Metrics
    4. Chapter 6 Preparing Data and Filtering
    5. Chapter 7 Clustering and Grouping
    6. Chapter 8 Email: The Lifeblood of Modern Communication
    7. Chapter 9 Thread Networks Mapping Message Boards and Email Lists
    8. Chapter 10 Twitter Conversation, Entertainment, and Information, All in One Network!
    9. Chapter 11 Visualizing and Interpreting Facebook Networks
    10. Chapter 12 WWW Hyperlink Networks
    11. Chapter 13 Flickr Linking People, Photos, and Tags
    12. Chapter 14 YouTube Contrasting Patterns of Content, Interaction, and Prominence
    13. Chapter 15 Wiki Networks Connections of Creativity and Collaboration
  10. IT 101 Lab: Analyzing Your Facebook or Twitter Network
    1. Purpose
    2. Procedures
      1. Step 1. Install NodeXL and importers
      2. Step 2. Use NodeXL to import the data you want to analyze 1
      3. Step 3. Create metrics and calculate clusters
      4. Step 4a. Visualize Your Network
      5. Step 4b. Fine-Tune Your Visualization
      6. Step 5. Create Your Final Visualization and Write-up
    3. ​​Reference
      1. 1
  11. NodeXL Help
    1. An Overview of Network Graphs
    2. A Quick Tour of the NodeXL Workbook
      1. The NodeXL Worksheets
      2. The Graph Pane
        1. The Graph Pane
        2. The Graph Legend
        3. The Graph Axes
      3. The NodeXL Ribbon Tab
    3. Creating a Simple Graph
    4. Directed vs. Undirected Graphs
    5. Graphs with Isolated Vertices
    6. Zooming, Moving Around and Scaling the Graph
      1. Zooming the Graph
      2. Moving Around the Graph
      3. Scaling the Graph
    7. Selecting Graph Elements
      1. Selecting Vertices
      2. Selecting Edges
    8. Changing How the Graph Looks
      1. Default Visual Properties: Graph Options
      2. Setting Visual Properties for Individual Edges, Vertices or Groups
      3. Automatically Calculating Visual Properties for All Edges, Vertices or Groups
      4. Labeling Edges, Vertices and Groups
    9. Changing How the Graph is Laid Out
      1. Layout Algorithms
      2. Selectively Laying Out Parts of the Graph Again
      3. Snapping Vertices to a Grid
      4. Layout Options
    10. Adding Tooltips to the Graph
    11. Saving an Image of the Graph
    12. Analyzing the Graph
      1. Calculating Graph Metrics
      2. Creating Subgraph Images
      3. Using Dynamic Filters
    13. Working with Options
      1. Using the Current Workbook's Options for New Workbooks
      2. Exporting and Importing Options
      3. Resetting All Options
    14. Working with Groups
      1. Creating Groups
        1. Creating Groups by Vertex Attribute
        2. Creating Groups by Connected Component
        3. Creating Groups by Cluster
        4. Creating Groups by Motif
        5. Manually Creating Groups
      2. Understanding the Group Worksheets
      3. How Groups Are Shown in the Graph Pane
        1. Color and Shape
        2. Group Layout
        3. Skipping All Groups
        4. Changing How Vertex Colors and Shapes are Specified
      4. Selecting Groups
      5. Collapsing and Expanding Groups
      6. Hiding and Skipping Groups
      7. Removing Groups
      8. Showing and Hiding Workbook Columns
      9. Showing and Hiding Graph Elements
      10. Summarizing the Graph
    15. Importing Graph Data
      1. Importing Graph Data from Other Programs
      2. Importing Graph Data from Another Workbook
      3. Importing Graph Data from Email
      4. Importing Graph Data from Online Social Networks
    16. Exporting Graph Data
      1. Exporting Graph Data to Other Programs
      2. Exporting Graph Data to Another Workbook
    17. Counting and Merging Duplicate Edges
    18. Automating Common Tasks
    19. Keyboard Shortcuts in the Graph Pane
    20. The NodeXL Network Server
    21. Where to Go for More Information
  12. Sci2 Tool
    1. A Tool for Science of Science Research & Practice
    2. News
    3. Please cite as
    4. Sci2 Help
    5. Acknowledgements
    6. Download
    7. Release Notes
    8. Supplemental Plugins
    9. SHOW ARCHIVED VERSIONS
    10. FAQ
    11. Sci2 Help
    12. Documentation
      1. User Manual and Handouts
      2. Classroom Usage
      3. Tutorials
      4. Publications
      5. Download Plugins from Other Tools
    13. Testimonials
    14. Scientific Publications that Use Sci2
  13. NEXT

Story

NodeXL Twitter Social Network Map for the #datacommunitydc

Marc Smith, Connected Action, makes the following offer:

If you would like to request a custom social media network map made with NodeXL for the topic, hashtag, URL, or username of your choice complete the form below.  I will generate the maps as requests come in and email you a pointer to the results which I will post to the NodeXL Graph Gallery: See - https://nodexlgraphgallery.org/Pages/Default.aspx

Request a NodeXL Twitter Social Network Map for the Topic of your Choice
Thanks!

Your response will now appear in my spreadsheet.

Marc ran a workshop at 1776dc last August and returned to 1776DC this Friday from 2-5 for a NodeXL user group meeting.

See: http://www.connectedaction.net/2014/03/07/april-4-2014-washington-dc-nodexl-user-group-meetup-at-tbd/

Below, is a copy of a recent map of the connections in Twitter among people who mentioned "DataCommunityDC".

Harlan Harris made the request for the Data Community DC tweets that used the hashtag "datacommunitydc"​ and got the spreadsheet, image below, and NodeXL Options file.

Here is your NodeXL Social Media Network Map and Report from Connected Action.

2014-04-03 06-02-44 NodeXL Twitter Search datacommunitydc.png

The graph represents a network of 56 Twitter users whose recent tweets contained "datacommunitydc", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Thursday, 03 April 2014 at 13:02 UTC.

The tweets in the network were tweeted over the 6-day, 23-hour, 28-minute period from Wednesday, 26 March 2014 at 23:58 UTC to Wednesday, 02 April 2014 at 23:27 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 is directed.

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.

Overall Graph Metrics:
Vertices: 56
Unique Edges: 92
Edges With Duplicates: 31
Total Edges: 123
Self-Loops: 4
Reciprocated Vertex Pair Ratio: 0.0625
Reciprocated Edge Ratio: 0.117647058823529
Connected Components: 4
Single-Vertex Connected Components: 2
Maximum Vertices in a Connected Component: 52
Maximum Edges in a Connected Component: 120
Maximum Geodesic Distance (Diameter): 4
Average Geodesic Distance: 2.262731
Graph Density: 0.0331168831168831
Modularity: 0.445948
NodeXL Version: 1.0.1.320

Top 10 Vertices, Ranked by Betweenness Centrality:
datacommunitydc
tandemnsi
harlanh
imrantech
aedbizinvest
iamjives
jon_m_rob
jakeporway
timmeko
seanmgonzalez

Top URLs in Tweet in Entire Graph:
http://datacommunitydc.org/blog/2014/03/newsletter-jobs/?utm_content=buffer56833&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
http://goo.gl/2Qstlv?utm_content=buffer10936&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
http://www.bizjournals.com/washington/blog/techflash/2014/03/hunch-analytics-nabsmicrostrategy-vet-bansal-as.html?ana=twt
http://www.eventbrite.com/e/tandemnsi-deal-day-registration-10157183409
http://datacommunitydc.org/blog/2014/03/deep-learning-inspires-deep-thinking/
https://tandemnsidealday.eventbrite.com/?discount=JIVES
http://datacommunitydc.org/blog/2014/03/deep-learning-inspires-deep-thinking/?utm_content=buffer643a2&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
http://datacommunitydc.org/blog/2014/03/newsletter-jobs/?utm_content=buffer3c921&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
http://www.bizjournals.com/washington/blog/techflash/2014/04/connectarlington-expansion-2014.html
http://datacommunitydc.org/blog/2014/03/deep-learning-inspires-deep-thinking/?utm_content=bufferc4c72&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

Top URLs in Tweet in G1:
http://datacommunitydc.org/blog/2014/03/newsletter-jobs/?utm_content=buffer56833&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
http://www.bizjournals.com/washington/blog/techflash/2014/04/connectarlington-expansion-2014.html
http://datacommunitydc.org/blog/2014/03/newsletter-jobs/?utm_content=buffer3c921&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
http://datacommunitydc.org/blog/2014/03/deep-learning-inspires-deep-thinking/?utm_content=buffer643a2&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
http://datacommunitydc.org/blog/2014/03/deep-learning-inspires-deep-thinking/
http://ow.ly/i/570Vn
http://goo.gl/2Qstlv?utm_content=buffer10936&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
https://www.surveymonkey.com/s/UT-InfoProSurvey?utm_content=bufferf8b0b&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
http://www.eventbrite.com/e/from-big-data-to-global-diplomacy-today-and-tomorrow-tickets-11090831977
http://www.bizjournals.com/washington/blog/techflash/2014/03/hunch-analytics-nabsmicrostrategy-vet-bansal-as.html?ana=twt

Top URLs in Tweet in G2:
http://www.bizjournals.com/washington/blog/techflash/2014/03/hunch-analytics-nabsmicrostrategy-vet-bansal-as.html?ana=twt
http://www.eventbrite.com/e/tandemnsi-deal-day-registration-10157183409
https://tandemnsidealday.eventbrite.com/?discount=JIVES

Top URLs in Tweet in G3:
http://datacommunitydc.org/blog/2014/03/newsletter-jobs/?utm_content=buffer56833&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
http://datacommunitydc.org/blog/2014/03/deep-learning-inspires-deep-thinking/?utm_content=bufferc4c72&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
http://us3.campaign-archive2.com/?u=75fc125999b198f97fe860a8d&id=eb9e132e86&e=83110738c2
https://datacommunitydc.wufoo.com/entries/dc2-job-ad-submission/

Top URLs in Tweet in G4:
http://goo.gl/2Qstlv?utm_content=buffer10936&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

Top URLs in Tweet in G5:
http://bigconf.io/schedule/index
https://docs.google.com/spreadsheet/pub?key=0Ag1jWvdrgwBxdDVMbHlRV1NmRF8ydkFHQjQ4bGl2T3c&output=html

Top URLs in Tweet in G6:
http://datacommunitydc.org/blog/2013/08/data-science-md-august-recap-sports-analytics-meetup/

Top URLs in Tweet in G7:
http://datacommunitydc.org/blog/2013/05/recommendation-engines-why-you-shouldnt-build-one/?utm_content=buffer5db21&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
http://datacommunitydc.org/blog/2014/03/deep-learning-inspires-deep-thinking/

Top Domains in Tweet in Entire Graph:
datacommunitydc.org
eventbrite.com
bizjournals.com
goo.gl
meetup.com
campaign-archive2.com
bigconf.io
ow.ly
iarpa.gov
wufoo.com

Top Domains in Tweet in G1:
datacommunitydc.org
eventbrite.com
bizjournals.com
meetup.com
ow.ly
goo.gl
surveymonkey.com
iarpa.gov

Top Domains in Tweet in G2:
eventbrite.com
bizjournals.com

Top Domains in Tweet in G3:
datacommunitydc.org
campaign-archive2.com
wufoo.com

Top Domains in Tweet in G4:
goo.gl

Top Domains in Tweet in G5:
bigconf.io
google.com

Top Domains in Tweet in G6:
datacommunitydc.org

Top Domains in Tweet in G7:
datacommunitydc.org

Top Hashtags in Tweet in Entire Graph:
datadc
dctech
arlingtonva
dealday
dataviz
datascience
business
innovation
dwdc
python

Top Hashtags in Tweet in G1:
datadc
dctech
datascience
arlingtonva
business
innovation
dwdc
dataviz
iarpa
instinct

Top Hashtags in Tweet in G2:
dctech
datadc
dealday
arlingtonva

Top Hashtags in Tweet in G3:
datadc

Top Hashtags in Tweet in G4:
dataviz

Top Hashtags in Tweet in G5:
tweetaid
bigdata
conf

Top Hashtags in Tweet in G7:
ecsusinn
deeplearning

Top Words in Tweet in Entire Graph:
datacommunitydc
datadc
rt
deep
dctech
data
newsletter
learning
jobs
dc

Top Words in Tweet in G1:
datadc
datacommunitydc
deep
data
via
rt
learning
out
jobs
great

Top Words in Tweet in G2:
dctech
datacommunitydc
datadc
5
7
dealday
hunchanalytics
nabs
microstrategy
vet

Top Words in Tweet in G3:
rt
datacommunitydc
newsletter
harlanh
deep
jobs
datadc
learning
inspires
thinking

Top Words in Tweet in G4:
dc
dataviz
wiz
kids
hiring
urbaninstitute
cc
jschwabish
timeplots
datacommunitydc

Top Words in Tweet in G5:
datacommunitydc
bigconf
schedule
door

Top Word Pairs in Tweet in Entire Graph:
deep,learning
dctech,datadc
newsletter,jobs
jobs,datadc
datacommunitydc,newsletter
dc,dataviz
dataviz,wiz
wiz,kids
kids,hiring
hiring,urbaninstitute

Top Word Pairs in Tweet in G1:
deep,learning
datadc,via
newsletter,jobs
jobs,datadc
dctech,datadc
datadc,datascience
via,harlanh
synglyphx,helping
helping,out
out,short

Top Word Pairs in Tweet in G2:
dctech,datadc
5,7
hunchanalytics,nabs
nabs,microstrategy
microstrategy,vet
vet,sanju
sanju,bansal
bansal,ceo
ceo,arlingtonva
arlingtonva,dctech

Top Word Pairs in Tweet in G3:
datacommunitydc,newsletter
rt,harlanh
newsletter,jobs
jobs,datadc
harlanh,datacommunitydc
deep,learning
learning,inspires
inspires,deep
deep,thinking
thinking,data

Top Word Pairs in Tweet in G4:
dc,dataviz
dataviz,wiz
wiz,kids
kids,hiring
hiring,urbaninstitute
urbaninstitute,cc
cc,jschwabish
jschwabish,timeplots
timeplots,datacommunitydc
rt,timmeko

Top Word Pairs in Tweet in G5:
bigconf,schedule

Top Replied-To in Entire Graph:
bigconf
seanmgonzalez
rabois
datacommunitydc

Top Replied-To in G3:
seanmgonzalez

Top Replied-To in G5:
bigconf
datacommunitydc

Top Replied-To in G6:
rabois

Top Mentioned in Entire Graph:
datacommunitydc
iamjives
harlanh
urbaninstitute
jschwabish
timeplots
hunchanalytics
timmeko
startup_va
tandemnsi

Top Mentioned in G1:
datacommunitydc
harlanh
iamjives
startup_va
tonyojeda3
synglyphx
rdempsey
timmeko
urbaninstitute
jschwabish

Top Mentioned in G2:
datacommunitydc
hunchanalytics
iamjives
datacommunit
novatechcouncil
fosterly
startup_va
campus_entre
uberoffices
iotdc

Top Mentioned in G3:
datacommunitydc
harlanh
datasciencedc
jon_m_rob
catalist_us
iamjives
aneeshchopra

Top Mentioned in G4:
urbaninstitute
jschwabish
timeplots
datacommunitydc
timmeko

Top Mentioned in G5:
datacommunitydc
bluelabs
silverspringmd

Top Mentioned in G7:
hpccsystems

Top Tweeters in Entire Graph:
usatoday
rdempsey
canastanooga
jburnmurdoch
waldojaquith
rabois
sunfoundation
dhgisme
neal_lathia
campus_entre

Top Tweeters in G1:
usatoday
rdempsey
waldojaquith
sunfoundation
pwang
stage_emploi
jakeporway
0x1983
artisphere
tonyojeda3

Top Tweeters in G2:
campus_entre
cofounderslab
aedbizinvest
novatechcouncil
startup_va
fosterly
seanmgonzalez
iamjives
uberoffices
iotdc

Top Tweeters in G3:
canastanooga
dhgisme
neal_lathia
harlanh
hyesookchung
jon_m_rob
aneeshchopra
catalist_us
datasciencedc

Top Tweeters in G4:
jburnmurdoch
urbaninstitute
zmcdade
jschwabish
grahamimac
timmeko
ooitsliz
timeplots

Top Tweeters in G5:
imrantech
silverspringmd
bluelabs
bigconf

Top Tweeters in G6:
rabois
jaredkrouss

Top Tweeters in G7:
hpccsystems
filipgoc

NodeXL on the web | Social Media Network Map and Report from Connected Action.
Request additional NodeXL Social Media Maps and Reports

Story

NodeXL Twitter Social Network Map for the #bigdataprivacy

Marc Smith, Connected Action, makes the following offer:

If you would like to request a custom social media network map made with NodeXL for the topic, hashtag, URL, or username of your choice complete the form below.  I will generate the maps as requests come in and email you a pointer to the results which I will post to the NodeXL Graph Gallery: See - https://nodexlgraphgallery.org/Pages/Default.aspx

Request a NodeXL Twitter Social Network Map for the Topic of your Choice
Thanks!

Your response will now appear in my spreadsheet.

I made the request for the White House - MIT Big Data and Privacy Workshop tweets that used the hashtag #bigdataprivacy in preparation for our Federal Big Data Working Group Meetup April 15th and got the spreadsheet, image below, and NodeXL Options file.

Here is your NodeXLSocial Media Network Map and Report from Connected Action.

2014-03-03 17-32-35 NodeXL Twitter Search #bigdataprivacy.png


The graph represents a network of 248 Twitter users whose recent tweets contained "#bigdataprivacy", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Tuesday, 04 March 2014 at 01:32 UTC.

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 is directed.

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.

Overall Graph Metrics:
Vertices: 248
Unique Edges: 523
Edges With Duplicates: 453
Total Edges: 976
Self-Loops: 205
Reciprocated Vertex Pair Ratio: 0.0416666666666667
Reciprocated Edge Ratio: 0.08
Connected Components: 13
Single-Vertex Connected Components: 7
Maximum Vertices in a Connected Component: 229
Maximum Edges in a Connected Component: 960
Maximum Geodesic Distance (Diameter): 6
Average Geodesic Distance: 2.957011
Graph Density: 0.00979495886117278
Modularity: 0.359753
NodeXL Version: 1.0.1.319

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

Top URLs in Tweet in G1:
http://web.mit.edu/bigdata-priv/webcast.html
http://thedatamap.org
http://www.foreignaffairs.com/articles/140741/craig-mundie/privacy-pragmatism
https://blogs.law.harvard.edu/billofhealth/2013/10/02/ethical-concerns-conduct-and-public-policy-for-re-identification-and-de-identification-practice-part-3-re-identification-symposium/
http://www.cs.ucdavis.edu/~franklin/ecs289/2010/dwork_2008.pdf
http://web.mit.edu/bigdata-priv/agenda.html
http://equalfuture.us/2014/02/26/chicago-police/
http://www.stanfordlawreview.org/online/privacy-and-big-data/buying-and-selling-privacy
http://www.cs.utexas.edu/~shmat/netflix-faq.html
http://www.futureofprivacy.org/wp-content/uploads/Brookman-Why-Collection-Matters.pdf

Top URLs in Tweet in G2:
http://www.commerce.gov/news/secretary-speeches/2014/03/03/us-secretary-commerce-penny-pritzker-delivers-remarks-mit
http://web.mit.edu/bigdata-priv/webcast.html
http://www.whitehouse.gov/blog/2014/02/24/privacy-workshop-explore-big-data-opportunities-challenges
http://www.msnbc.com/morning-joe/watch/commerce-dept-focuses-on-job-creation-179963459586
http://web.mit.edu/newsoffice/2014/white-house-to-co-host-workshop-at-mit-on-big-data-and-privacy.html
http://www.wired.com/wiredenterprise/2014/03/jeeves/?utm_content=bufferb13fe&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
http://en.m.wikipedia.org/wiki/Herman_Hollerith
http://www.scotsman.com/news/data-privacy-the-big-challenge-in-healthcare-1-3325980#.UxSNbU53b08.twitter
http://lawreview.colorado.edu/wp-content/uploads/2013/11/13.-Wu_710_s.pdf
https://en.wikipedia.org/wiki/Francis_Amasa_Walker

Top URLs in Tweet in G3:
http://web.mit.edu/bigdata-priv/webcast.html
http://www.cmu.edu/simon/datalab/
http://www.commerce.gov/news/secretary-speeches/2014/03/03/us-secretary-commerce-penny-pritzker-delivers-remarks-mit

Top URLs in Tweet in G4:
http://web.mit.edu/bigdata-priv/webcast.html
http://web.mit.edu/bigdata-priv/agenda.html
http://thedatamap.org/
https://www.constellationr.com/content/strengths-and-weaknesses-data-privacy-age-big-data
http://lockstep.com.au/blog/2012/10/29/not-too-late-for-privacy
http://lockstep.com.au/blog/2011/01/26/public-yet-still-private
http://www.cs.ucdavis.edu/~franklin/ecs289/2010/dwork_2008.pdf
http://www.commerce.gov/news/secretary-speeches/2014/03/03/us-secretary-commerce-penny-pritzker-delivers-remarks-mit
http://www.msnbc.com/morning-joe/watch/commerce-dept-focuses-on-job-creation-179963459586
http://www.ecitizen.tv/2014/01/this-is-your-identity-on-big-data.html

Top URLs in Tweet in G5:
http://m.technologyreview.com/news/525131/intel-designs-a-safe-meeting-place-for-private-data/
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://en.wikipedia.org/wiki/Federal_Information_Processing_Standards
http://towcenter.org/blog/the-effects-of-mass-surveillance-on-journalism/
http://radar.oreilly.com/2013/04/predictive-big-data-analytics-privacy.html
http://web.mit.edu/bigdata-priv/webcast.html

Top URLs in Tweet in G6:
http://web.mit.edu/bigdata-priv/webcast.html?utm_source=hootsuite&utm_campaign=hootsuite
http://tech.mit.edu/V134/N8/fsilg.html
http://web.mit.edu/bigdata-priv/webcast.html
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/

Top URLs in Tweet in G7:
http://web.mit.edu/bigdata-priv/webcast.html
http://web.mit.edu/bigdata-priv/agenda.html

Top URLs in Tweet in G8:
http://www.commvault.com/news/blogs/437-commvault-software-helps-protect-real-time-analytics-environments

Top Domains in Tweet in Entire Graph:
mit.edu
commerce.gov
wikipedia.org
whitehouse.gov
nytimes.com
thedatamap.org
techrepublic.com
technologyreview.com
foreignaffairs.com
ucdavis.edu

Top Domains in Tweet in G1:
mit.edu
thedatamap.org
foreignaffairs.com
wikipedia.org
harvard.edu
ucdavis.edu
equalfuture.us
stanfordlawreview.org
utexas.edu
futureofprivacy.org

Top Domains in Tweet in G2:
commerce.gov
mit.edu
whitehouse.gov
msnbc.com
wikipedia.org
wired.com
scotsman.com
colorado.edu
nytimes.com
techrepublic.com

Top Domains in Tweet in G3:
mit.edu
cmu.edu
commerce.gov

Top Domains in Tweet in G4:
mit.edu
ecitizen.tv
thedatamap.org
com.au
constellationr.com
ucdavis.edu
commerce.gov
msnbc.com

Top Domains in Tweet in G5:
technologyreview.com
nytimes.com
techrepublic.com
wikipedia.org
towcenter.org
oreilly.com
mit.edu

Top Domains in Tweet in G6:
mit.edu
nytimes.com
techrepublic.com

Top Domains in Tweet in G7:
mit.edu

Top Domains in Tweet in G8:
commvault.com

Top Hashtags in Tweet in Entire Graph:
bigdataprivacy
privacy
mit
bigdata
mass_tech
infoaccountability
iot
pbd
pii
nsa

Top Hashtags in Tweet in G1:
bigdataprivacy
privacy
mit
bigdata
infoaccountability
cambma
differentialprivacy
edx
iot
foreignaffairs

Top Hashtags in Tweet in G2:
bigdataprivacy
bigdata
mit
privacy
mass_tech
infoaccountability
health
nsa
compliance
bigdatamit

Top Hashtags in Tweet in G3:
bigdataprivacy
mit
bigdata

Top Hashtags in Tweet in G4:
bigdataprivacy
privacy
bigdata
mass_tech
pbd
pii
hipaa
mit
bigdataidentity
newdealondata

Top Hashtags in Tweet in G5:
bigdataprivacy
privacy
iot

Top Hashtags in Tweet in G6:
bigdataprivacy
bigdata
privacy
iot

Top Hashtags in Tweet in G7:
bigdataprivacy
privacy
mit

Top Hashtags in Tweet in G8:
simpana
sap
hana
analytics
bigdataprivacy

Top Hashtags in Tweet in G9:
bigdataprivacy
seen

Top Hashtags in Tweet in G10:
bigdataprivacy

Top Words in Tweet in Entire Graph:
bigdataprivacy
privacy
data
mit
whitehouseostp
workshop
big
mit_csail
talk
pennypritzker

Top Words in Tweet in G1:
bigdataprivacy
privacy
data
big
mit
dwork
podesta
more
john
stannenb

Top Words in Tweet in G2:
bigdataprivacy
mit
pennypritzker
mit_csail
talk
whitehouseostp
workshop
data
mt
privacy

Top Words in Tweet in G3:
whitehouseostp
mit
bigdataprivacy
workshop
tune
live
starting
watch
9am
here

Top Words in Tweet in G4:
bigdataprivacy
privacy
data
mit
steve_lockstep
live
collection
bigdata
now
smwat

Top Words in Tweet in G5:
bigdataprivacy
data
digiphile
privacy
intel
designs
safe
meeting
place
private

Top Words in Tweet in G6:
bigdataprivacy
data
privacy
big
mit
workshop
white
house

Top Words in Tweet in G7:
bigdataprivacy
white
house
mit
privacy
workshop
2
watching
big
data

Top Words in Tweet in G9:
bigdataprivacy

Top Words in Tweet in G10:
data
university

Top Word Pairs in Tweet in Entire Graph:
big,data
whitehouseostp,mit
mit,workshop
bigdataprivacy,workshop
workshop,bigdataprivacy
tune,live
live,whitehouseostp
whitehouseostp,tune
john,podesta
differential,privacy

Top Word Pairs in Tweet in G1:
big,data
differential,privacy
john,podesta
cynthia,dwork
bigdataprivacy,event
privacy,bigdataprivacy
data,sets
2nd,big
big,policymaker
policymaker,takeaway

Top Word Pairs in Tweet in G2:
pennypritzker,mit
mit,talk
talk,business
business,university
university,leaders
leaders,bigdataprivacy
bigdataprivacy,principles
principles,trust
mit,mt
mt,mit_csail

Top Word Pairs in Tweet in G3:
whitehouseostp,mit
tune,live
live,whitehouseostp
mit,workshop
workshop,bigdataprivacy
whitehouseostp,tune
mit,whitehouseostp
watch,whitehouseostp
mit,bigdataprivacy
bigdataprivacy,workshop

Top Word Pairs in Tweet in G4:
outstanding,bigdata
bigdata,privacy
privacy,panel
panel,live
live,streaming
streaming,mit
mit,right
right,now
correlations,reveal
reveal,patterns

Top Word Pairs in Tweet in G5:
intel,designs
designs,safe
safe,meeting
meeting,place
place,private
private,data
data,tsimonite
tsimonite,lt
lt,potential
potential,bigdataprivacy

Top Word Pairs in Tweet in G6:
big,data
data,privacy
privacy,workshop
white,house
mit,bigdataprivacy

Top Word Pairs in Tweet in G7:
white,house
watching,white
house,mit
mit,big
big,data
data,privacy
privacy,workshop
workshop,video
video,agenda
adamthierer,watching

Top Replied-To in Entire Graph:
djweitzner
blairreeves
digiphile
mikaelf
andyhpalmer
joejerome
iotstockholm
chesterj1
andrewproia
pawal

Top Replied-To in G1:
djweitzner
joejerome
mikaelf
digiphile
iotstockholm
pawal
chesterj1
stannenb
mit
jv_kennedy

Top Replied-To in G2:
djweitzner
andyhpalmer

Top Replied-To in G5:
blairreeves
djweitzner

Top Replied-To in G8:
sapinmemory

Top Replied-To in G9:
informor
seentracker

Top Mentioned in Entire Graph:
mit
whitehouseostp
mit_csail
pennypritzker
stannenb
djweitzner
harlanyu
dbarthjones
digiphile
agarwaledu

Top Mentioned in G1:
stannenb
harlanyu
djweitzner
dbarthjones
mit_csail
mit
mikaelf
dispositive
joejerome
whitehouseostp

Top Mentioned in G2:
mit
pennypritzker
mit_csail
whitehouseostp
agarwaledu
morning_joe
hopley
djweitzner
stannenb
wired

Top Mentioned in G3:
whitehouseostp
mit
mit_csail
pennypritzker
scsatcmu
mitevents
ecampusnews

Top Mentioned in G4:
steve_lockstep
smwat
mit_csail
whitehouseostp
pennypritzker
hopley
karenkornbluh
batnib
stannenb
latanyasweeney

Top Mentioned in G5:
digiphile
tsimonite
johnpodesta
mit_csail
whitehouse
richelmore
claudiawilliams

Top Mentioned in G6:
mona_vernon

Top Mentioned in G7:
adamthierer
aureliepols
whitehouseostp

Top Mentioned in G8:
commvault

Top Mentioned in G10:
gigabarb
gigaom

Top Tweeters in Entire Graph:
datachick
digiphile
lawey
ohhsocialmedia
darnell_lockett
dominiquevanpee
ewrmadrid
brianmoran
gigaom
musiccloset2012

Top Tweeters in G1:
shyduroff
joebeone
gigabarb
pernillan
p2173
infomgmtexec
jahendler
privatelocknet
altheimlaw
copylinda

Top Tweeters in G2:
darnell_lockett
dominiquevanpee
ewrmadrid
brianmoran
musiccloset2012
ggheorghiu
wired
govillage
morning_joe
commercegov

Top Tweeters in G3:
datachick
lawey
mezgravis
sirtigerhai
inivisible
ayannamonte
casparbowden
jmillerwfed
oh_jorji
ecampusnews

Top Tweeters in G4:
jackwmson
holgermu
ifnhaa
steve_lockstep
futureidentity
robertspaige
augustmuench
apicot
orgnet
frumioj

Top Tweeters in G5:
digiphile
ohhsocialmedia
ianbrownoii
whitehouse
herr_arendt
rasushrestha
tnhh
ewhitmore
doccomltd
tsimonite

Top Tweeters in G6:
knieriemen
andrewlipstein
bsegalis
researchpays
micmickimo
iotobj
micosmin

Top Tweeters in G7:
adamthierer
iethics
jbsay
raekaaiyar
fortumconsultan

Top Tweeters in G8:
commvault
sapinmemory
terencehuggins

Top Tweeters in G9:
seenfeed
informor
seentracker

Top Tweeters in G10:
gigaom
mercuryglobal

NodeXL on the web | Social Media Network Map and Report from Connected Action.
Request additional NodeXL Social Media Maps and Reports

Slides

NodeXL

GraphML File Processor

GraphML File Processor.png

GraphML File Processor Message

GraphML File Processor Help.png

NodeXL Interface

NodeXL Excel Template.png

Help

Help.png

Slide 1 Charting Collections of Connections in Social Media with NodeXL

Source: http://www.slideshare.net/Marc_A_Smi...twork-analysis

Also: http://www.slideshare.net/Marc_A_Smi...mediaformatted

My Note: Slide 13: A network is born whenever two GUIDs are joined. 

A

Username Attributes
@UserName1 Value, value

B

Username Attributes
@UserName2 Value, value

 

Vertex1 Vertex 2  “Edge” Attribute “Vertex1” Attribute “Vertex2” Attribute
@UserName1 @UserName2 value value value

Bill Anton (@SQLbyoBI)HOW TO BUILD a table of all the object dependencies in a database

http://byobi.com/blog/2013/03/analyz...s-with-nodexl/

 

MarcSmith08302011Slide1.PNG

Slide 2 About Me

MarcSmith08302011Slide2.PNG

Slide 3 Social Media Research Foundation Map

MarcSmith08302011Slide3.PNG

Slide 15 Social Networks

MarcSmith08302011Slide15.PNG

Slide 17 Social Media Research Foundation

MarcSmith08302011Slide17.PNG

Slide 18 Introduction to NodeXL

MarcSmith08302011Slide18.PNG

Slide 19 Network Analysis Data Flow

MarcSmith08302011Slide19.PNG

Slide 29 NodeXL Graph Gallery

MarcSmith08302011Slide29.PNG

Slide 30 Social Network Maps Reveal

MarcSmith08302011Slide30.PNG

Slide 37 NodeXL Add-in for Excel 2007/2010

MarcSmith08302011Slide37.PNG

Slide 39 Six Kinds of Twitter Social Media Networks

MarcSmith08302011Slide39.PNG

Slide 47 Social Network Theory

MarcSmith08302011Slide47.PNG

Slide 48 SNA 101

MarcSmith08302011Slide48.PNG

Slide 49 NodeXL Senate Data Example

MarcSmith08302011Slide49.PNG

Slide 51 Goal: Make SNA Easier

MarcSmith08302011Slide51.PNG

Slide 55 NodeXL Graph Gallery

MarcSmith08302011Slide55.PNG

Slide 56 Book Now Available

MarcSmith08302011Slide56.PNG

Slide 62 NodeXL Calculates Network Metrics and Word Pairs

MarcSmith08302011Slide62.PNG

Slide 70 NodeXL Data Import Sources

MarcSmith08302011Slide70.PNG

Slide 82 Social Media Research Foundation Matrix

MarcSmith08302011Slide82.PNG

Slide 83 What We Are Trying To Do

MarcSmith08302011Slide83.PNG

Slide 88 What We Want To Do

MarcSmith08302011Slide88.PNG

Sci2 Tool

Sci2FileStructure1.png

Sci2FileStructure2.png

Sci2OpeningScreen1.png

Sci2OpeningScreen2.png

Sci2OpeningScreen3.png

Sci2OpeningScreen4.png

Spotfire Dashboard

Research Notes

http://en.wikipedia.org/wiki/Graph_theory

http://en.wikipedia.org/wiki/Social_network

http://ivl.cns.iu.edu/km/news-extern...tion-today.pdf (PDF)

NodeXL arranges the group boxes in what is called a squarified treemap

http://casci.umd.edu/NodeXL_Teaching My Note: Not found, but see other below

http://casci.umd.edu/research-resour...-tools/nodexl/

http://www.peteraldhous.com/CAR/NodeXL_CAR2012.pdf (PDF)

The newest NodeXL is v.320.  See: http://nodexl.codeplex.com/releases/view/117659

Note! If you are running an earlier version of NodeXL you MUST UNINSTALL the application prior to installing this version.

This version has "auto-update", making this the last time you will need to upgrade the application manually.

The "web version" is not really built yet. NodeXLGraphGallery.org does feature an "experimental" web visualization of the network that is minimally interactive.  See: https://www.nodexlgraphgallery.org/Pages/InteractiveGraph.aspx?graphID=18281 for an example.

We do plan to enable more work flow without requiring Windows+Office+Excel+NodeXL.  A minimal form of this is enabled by the blog post request form at: http://www.connectedaction.net/2010/06/13/request-a-nodexl-social-media-network-map/

NodeXL

NodeXL Release Notes, Version 1.0.1.251 (2014-01-14)

* Bug fix: If you attempted to import a Twitter network on January 14, 2014 or later, you would get an error message that included the text "The remote server returned an error: (403) Forbidden."

* It now takes significantly less time to import a graph from the NodeXL Graph Server. (This is a server-side change, so you don't need version 1.0.1.251 to notice the difference.)

* Graphs imported from the NodeXL Graph Server now include vertices for people who were replied to or mentioned by the people who tweeted the specified term but who didn't tweet the term themselves. (Note 1: Collection of the additional vertices started on 2013-08-21. Networks that span earlier dates might include some additional vertices if they happen to already be in the collection database. Note 2: This is a server-side change, so you don't need version 1.0.1.251 to notice the difference.)

To use the NodeXL Excel Template, do the following:
·    In the Windows Start menu, click "All Programs" (in Windows 7 or Vista) or "Programs" (in XP), then " NodeXL.”
·    Click “NodeXL Excel Template.”

NodeXL Graph Gallery: See a graph of interest and select it

 
putin search on Twitter (unlimited)
From:
SHJ
Uploaded on:
March 01, 2014
Description:
The graph is directed.

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.

Overall Graph Metrics:
Vertices: 273
Unique Edges: 0
Edges With Duplicates: 0
Total Edges: 0
Self-Loops: 0
Reciprocated Vertex Pair Ratio: Not Applicable
Reciprocated Edge Ratio: Not Applicable
Connected Components: 273
Single-Vertex Connected Components: 273
Maximum Vertices in a Connected Component: 1
Maximum Edges in a Connected Component: 0
Maximum Geodesic Distance (Diameter): Not Applicable
Average Geodesic Distance: Not Applicable
Graph Density: 0
Modularity: Not Applicable
NodeXL Version: 1.0.1.319

Top Tweeters in Entire Graph:
easy_branches
telesurtv
tuboyfriiend
filterednews
andrierpe
news1nfo
tuboyfriiend_ii
owillis
dorothylamar
lawsonbulk
 
About NodeXL Workbooks

The data for this graph is available as a NodeXL workbook. If you are a NodeXL user, you can download the workbook, open it in Microsoft® Excel® 2007 or 2010, and view the graph in an interactive window.

A few important points about downloading a NodeXL workbook:

  • If you are asked whether you want to save the NodeXL workbook or open it, choose the "save" option. For security reasons, Excel will not open a NodeXL workbook that hasn't been saved first.
  • NodeXL must be installed on your computer before you can open the downloaded NodeXL workbook in Excel®. If you haven't already done so, you can download NodeXL from here.
 
About GraphML

The data for this graph is available as GraphML, which is a standard file format for storing network graphs. If you are a NodeXLuser, you can download the GraphML file and then import it into NodeXL.

To import the downloaded GraphML file into NodeXL, use the following item in the Excel® ribbon:

  • NodeXL, Data, Import, From GraphML File

You can also import the GraphML file into any other program that supports the GraphML file format.

 
About NodeXL Options

The NodeXL options that were used to create this graph are available as a NodeXL options file. The options determined the graph colors, vertex shapes, edge widths, layout algorithm and many other graph characteristics.

If you are a NodeXL user, you can download the NodeXL options file and then import it into your own NodeXL workbook. Your graph will then have the same colors, vertex shapes, edge widths, layout algorithm and so on.

To import the downloaded NodeXL options file into a NodeXL workbook, use the following item in the Excel® ribbon:

  • NodeXL, Options, Import

Once you have imported the NodeXL options file into a NodeXL workbook, you can tell NodeXL to use these options for all new NodeXL workbooks that you create. To do that, use the following item in the Excel® ribbon:

  • NodeXL, Options, Use Current for New

Sci2 Tool

A more complete set of sample data is available individually or as a complete zip on the Sci2 Wiki located at: 
http://wiki.cns.iu.edu/display/SCI2T...ample+Datasets My Note: I used these sample data sets in Spotfire

NodeXL: Network Overview, Discovery and Exploration for Excel

Source: http://nodexl.codeplex.com/

Last edited Feb 11 at 12:46 PM by MarcSmith, version 503

 

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