Google nyc-6-3-2011

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Talk in Google- NYC, 6/3/2011 covering Information Visualization Analyzing Social Media Networks with NodeXL

Transcript of Google nyc-6-3-2011

Analyzing Social Media Networkswith NodeXL

Ben Shneiderman ben@cs.umd.edu @benbendc

Founding Director (1983-2000), Human-Computer Interaction LabProfessor, Department of Computer Science

Member, Institute for Advanced Computer Studies

University of MarylandCollege Park, MD 20742

Interdisciplinary research community - Computer Science & Info Studies - Psych, Socio, Poli Sci & MITH (www.cs.umd.edu/hcil)

Design Issues

• Input devices & strategies• Keyboards, pointing devices, voice

• Direct manipulation

• Menus, forms, commands

• Output devices & formats• Screens, windows, color, sound

• Text, tables, graphics

• Instructions, messages, help

• Collaboration & Social Media

• Help, tutorials, training

• Search www.awl.com/DTUI

Fifth Edition: 2010

• Visualization

Information Visualization

• Visual bandwidth is enormous• Human perceptual skills are remarkable

• Trend, cluster, gap, outlier...

• Color, size, shape, proximity...

• Three challenges• Meaningful visual displays of massive data

• Interaction: widgets & window coordination

• Process models for discovery:

Leader in Info Visualization

Business takes action

• General Dynamics buys MayaViz

• Agilent buys GeneSpring

• Google buys Gapminder

• Oracle buys Hyperion

• Microsoft buys Proclarity

• InfoBuilders buys Advizor Solutions

• SAP buys (Business Objects buys Xcelsius & Inxight & Crystal Reports )

• IBM buys (Cognos buys Celequest) & ILOG

• TIBCO buys Spotfire

Spotfire: Retinol’s role in embryos & vision

http://registration.spotfire.com/eval/default_edu.asp

10M - 100M pixels

Large displays for single or multiple users

100M-pixels & more

1M-pixels & less

Small mobile devices

Information Visualization: Mantra

• Overview, zoom & filter, details-on-demand

• Overview, zoom & filter, details-on-demand

• Overview, zoom & filter, details-on-demand

• Overview, zoom & filter, details-on-demand

• Overview, zoom & filter, details-on-demand

• Overview, zoom & filter, details-on-demand

• Overview, zoom & filter, details-on-demand

• Overview, zoom & filter, details-on-demand

• Overview, zoom & filter, details-on-demand

• Overview, zoom & filter, details-on-demand

Information Visualization: Data Types

• 1-D Linear Document Lens, SeeSoft, Info Mural

• 2-D Map GIS, ArcView, PageMaker, Medical imagery

• 3-D World CAD, Medical, Molecules, Architecture

• Multi-Var Spotfire, Tableau, GGobi, TableLens, ParCoords,

• Temporal LifeLines, TimeSearcher, Palantir, DataMontage

• Tree Cone/Cam/Hyperbolic, SpaceTree, Treemap

• Network Pajek, JUNG, UCINet, SocialAction, NodeXL

I

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infosthetics.com flowingdata.com infovis.org eagereyes.org www.infovis.net/index.php?lang=2

Anscombe’s Quartet

1 2 3 4

x y x y x y x y

10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58

8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76

13.0 7.58 13.0 8.74 13.0 12.74 8.0 7.71

9.0 8.81 9.0 8.77 9.0 7.11 8.0 8.84

11.0 8.33 11.0 9.26 11.0 7.81 8.0 8.47

14.0 9.96 14.0 8.10 14.0 8.84 8.0 7.04

6.0 7.24 6.0 6.13 6.0 6.08 8.0 5.25

4.0 4.26 4.0 3.10 4.0 5.39 19.0 12.50

12.0 10.84 12.0 9.13 12.0 8.15 8.0 5.56

7.0 4.82 7.0 7.26 7.0 6.42 8.0 7.91

5.0 5.68 5.0 4.74 5.0 5.73 8.0 6.89

Anscombe’s Quartet

1 2 3 4

x y x y x y x y

10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58

8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76

13.0 7.58 13.0 8.74 13.0 12.74 8.0 7.71

9.0 8.81 9.0 8.77 9.0 7.11 8.0 8.84

11.0 8.33 11.0 9.26 11.0 7.81 8.0 8.47

14.0 9.96 14.0 8.10 14.0 8.84 8.0 7.04

6.0 7.24 6.0 6.13 6.0 6.08 8.0 5.25

4.0 4.26 4.0 3.10 4.0 5.39 19.0 12.50

12.0 10.84 12.0 9.13 12.0 8.15 8.0 5.56

7.0 4.82 7.0 7.26 7.0 6.42 8.0 7.91

5.0 5.68 5.0 4.74 5.0 5.73 8.0 6.89

Property Value

Mean of x  9.0

Variance of x 11.0

Mean of y  7.5

Variance of y  4.12

Correlation 0.816

Linear regression y = 3 + 0.5x

Anscombe’s Quartet

Temporal Data: TimeSearcher 1.3

• Time series• Stocks

• Weather

• Genes

• User-specified patterns

• Rapid search

Temporal Data: TimeSearcher 2.0

• Long Time series (>10,000 time points)

• Multiple variables

• Controlled precision in match (Linear, offset, noise, amplitude)

LifeLines: Patient Histories

www.cs.umd.edu/hcil/lifelines

LifeLines2: Contrast+Creatine

LifeLines2: Align-Rank-Filter & Summarize

Treemap: Gene Ontology

www.cs.umd.edu/hcil/treemap/

+ Space filling

+ Space limited

+ Color coding

+ Size coding - Requires learning

(Shneiderman, ACM Trans. on Graphics, 1992 & 2003)

www.smartmoney.com/marketmap

Treemap: Smartmoney MarketMap

Market falls steeply Feb 27, 2007, with one exception

Market mixed, February 8, 2008 Energy & Technology up, Financial & Health Care down

Market rises, September 1, 2010, Gold contrarians

Market rises, March 21, 2011, Sprint declines

newsmap.jp

Treemap: Newsmap (Marcos Weskamp)

www.hivegroup.com

Treemap: Supply Chain

www.spotfire.com

Treemap: Spotfire Bond Portfolio Analysis

Treemap: NY Times – Car&Truck Sales

www.cs.umd.edu/hcil/treemap/

Treemap (Voronoi): NY Times - Inflation

www.nytimes.com/interactive/2008/05/03/business/20080403_SPENDING_GRAPHIC.html

State-of-the-art network visualization

Discovery Process: Systematic Yet Flexible

Preparation• Own the problem & define the schedule• Data cleaning & conditioning• Handle missing & uncertain data• Extract subsets & link to related information

SocialAction

• Integrates statistics & visualization

• 4 case studies, 4-8 weeks (journalist, bibliometrician, terrorist analyst, organizational analyst)

• Identified desired features, gave strong positive feedback about benefits of integration

Perer & Shneiderman, CHI2008, IEEE CG&A 2009www.cs.umd.edu/hcil/socialaction

Footprints of Human Activity

• Footprints in sand as Caesarea

NodeXL: Network Overview for Discovery & Exploration in Excel

www.codeplex.com/nodexl

NodeXL: Network Overview for Discovery & Exploration in Excel

www.codeplex.com/nodexl

NodeXL: Import Dialogs

www.codeplex.com/nodexl

Tweets at #WIN09 Conference: 2 groups

WWW2010 Twitter Community

WWW2011 Twitter Community: Grouped

Tweets for #HCI: 2 groups

CHI2010 Twitter Community

www.codeplex.com/nodexl/

Oil Spill Twitter Community

www.codeplex.com/nodexl/

‘GOP’ tweets, clustered (red-Republicans)

Flickr clusters for “mouse”

Computer Mickey

Animal

Flickr networks

Co-author network for HCIL tech reports

Vertices sized by number of papers. Edges sized number of co-authored reports. Colored by clustering.

Co-author network for HCIL tech reports

Vertices sized by number of papers, edges sized number of co-authored reports

Colored by date of first paper.

Includes only those with at least 5 co-authored papers.

Nation of Neighbors Discussion Groups

Analyzing Social Media Networks with NodeXL

I. Getting Started with Analyzing Social Media Networks 1. Introduction to Social Media and Social Networks 2. Social media: New Technologies of Collaboration 3. Social Network Analysis

II. NodeXL Tutorial: Learning by Doing 4. Layout, Visual Design & Labeling 5. Calculating & Visualizing Network Metrics  6. Preparing Data & Filtering 7. Clustering &Grouping

III Social Media Network Analysis Case Studies 8. Email 9. Threaded Networks 10. Twitter 11. Facebook   12. WWW 13. Flickr 14. YouTube  15. Wiki Networks 

www.elsevier.com/wps/find/bookdescription.cws_home/723354/description

Social Media Research Foundation

Researchers who want to - create open tools - generate & host open data - support open scholarship

Map, measure & understand social media  

Support tool projects to collection, analyze & visualize social media data.  

smrfoundation.org

UN Millennium Development Goals

• Eradicate extreme poverty and hunger• Achieve universal primary education• Promote gender equality and empower women• Reduce child mortality• Improve maternal health• Combat HIV/AIDS, malaria and other diseases• Ensure environmental sustainability• Develop a global partnership for development

To be achieved by 2015

Just happened: 28th Annual SymposiumMay 25-26, 2011

Next Event: Summer Social WebshopAugust 23-26, 2011

(Sponsored by NSF & Google)www.cs.umd.edu/hcil/webshop2011

For More Information

• Visit the HCIL website for 400 papers & info on videos www.cs.umd.edu/hcil

• Conferences & resources: www.infovis.org

• See Chapter 14 on Info Visualization Shneiderman, B. and Plaisant, C., Designing the User Interface: Strategies for Effective Human-Computer Interaction: Fifth Edition (March 2009) www.awl.com/DTUI

• Edited Collections: Card, S., Mackinlay, J., and Shneiderman, B. (1999) Readings in Information Visualization: Using Vision to Think Bederson, B. and Shneiderman, B. (2003) The Craft of Information Visualization: Readings and Reflections

For More Information

• Treemaps• HiveGroup: www.hivegroup.com • Smartmoney: www.smartmoney.com/marketmap • HCIL Treemap 4.0: www.cs.umd.edu/hcil/treemap

• Spotfire: www.spotfire.com • TimeSearcher: www.cs.umd.edu/hcil/timesearcher • NodeXL: nodexl.codeplex.com• Hierarchical Clustering Explorer:

www.cs.umd.edu/hcil/hce

• LifeLines2: www.cs.umd.edu/hcil/lifelines2 • Similan: www.cs.umd.edu/hcil/similan