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NetworkMapsfor EndUsers: Collect,Analyze, Visualizeand … · 2011-10-19 · A"projectfrom"the"...
Transcript of NetworkMapsfor EndUsers: Collect,Analyze, Visualizeand … · 2011-10-19 · A"projectfrom"the"...
A project from the Social Media Research Founda8on: h:p://www.smrfounda8on.org
Network Maps for End Users:
Collect, Analyze, Visualize and Communicate
Network Insights with Zero Coding
About Me
Introduc8ons Marc A. Smith Chief Social Scien8st Connected Ac8on Consul8ng Group [email protected] h:p://www.connectedac8on.net h:p://www.codeplex.com/nodexl h:p://www.twi:er.com/marc_smith h:p://delicious.com/marc_smith/Paper h:p://www.flickr.com/photos/marc_smith h:p://www.facebook.com/marc.smith.sociologist h:p://www.linkedin.com/in/marcasmith h:p://www.slideshare.net/Marc_A_Smith h:p://www.smrfounda8on.org
h:p://www.flickr.com/photos/library_of_congress/3295494976/sizes/o/in/photostream/
h:p://www.flickr.com/photos/amycgx/3119640267/
• Central tenet – Social structure emerges from – the aggregate of rela8onships (8es) – among members of a popula8on
• Phenomena of interest – Emergence of cliques and clusters – from pa:erns of rela8onships – Centrality (core), periphery (isolates), – betweenness
• Methods – Surveys, interviews, observa8ons,
log file analysis, computa8onal analysis of matrices
(Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001)
Source: Richards, W. (1986). The NEGOPY network analysis program. Burnaby, BC: Department of Communica8on, Simon Fraser University. pp.7-‐16
Social Network Theory h:p://en.wikipedia.org/wiki/Social_network
SNA 101 • Node
– “actor” on which rela8onships act; 1-‐mode versus 2-‐mode networks • Edge
– Rela8onship connec8ng nodes; can be direc8onal • Cohesive Sub-‐Group
– Well-‐connected group; clique; cluster • Key Metrics
– Centrality (group or individual measure) • Number of direct connec8ons that individuals have with others in the group (usually look at incoming connec8ons only)
• Measure at the individual node or group level – Cohesion (group measure)
• Ease with which a network can connect • Aggregate measure of shortest path between each node pair at network level reflects average distance
– Density (group measure) • Robustness of the network • Number of connec8ons that exist in the group out of 100% possible
– Betweenness (individual measure) • # shortest paths between each node pair that a node is on • Measure at the individual node level
• Node roles – Peripheral – below average centrality – Central connector – above average centrality – Broker – above average betweenness
E
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A B D E
Email (and more) is from people to people 8
PaDerns are leE behind
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There are many kinds of 8es….
h:p://www.flickr.com/photos/stevendepolo/3254238329
World Wide Web
Each contains one or more social networks
Welser, Howard T., Eric Gleave, Danyel Fisher, and Marc Smith. 2007. Visualizing the Signatures of Social Roles in Online Discussion Groups. The Journal of Social Structure. 8(2).
Experts and “Answer People”
Discussion starters, Topic se:ers
Discussion people, Topic se:ers
Tag Ecologies I
Adamic et al. WWW 2008
HUB-‐AND-‐SPOKE OF DECEIT: When Enron employees communicated about legi8mate projects, e-‐mails were reciprocal and informa8on was shared widely (right), but communica8ons about an illicit project (les) reveal a sparse network with a central, informed clique and isolated external players. Brandy Aven, CMU h:p://www.sciencenews.org/view/generic/id/330731/8tle/Informa8on_flow_can_reveal_dirty_deeds
Networks reveal pa:erns
Goal: Make SNA easier
• Exis8ng Social Network Tools are challenging for many novice users
• Tools like Excel are widely used • Leveraging a spreadsheet as a host for SNA lowers barriers to network data analysis and display
Who we are People Disciplines InsGtuGons
University Faculty
Computer Science University of Maryland
Students HCI, CSCW Oxford Internet Ins8tute
Industry Machine Learning Stanford University
Independent Informa8on Visualiza8on
Microsos Research
Researchers UI/UX Illinois Ins8tute of Technology
Developers Social Science/Sociology Connected Ac8on
Network Analysis Cornell
Collec8ve Ac8on Morningside Analy8cs
What we are trying to do: Open Tools, Open Data, Open Scholarship • Build the “Firefox of GraphML” – open tools for collec8ng and visualizing social media data
• Connect users to network analysis – make network charts as easy as making a pie chart
• Connect researchers to social media data sources • Archive: Be the “Allen Very Large Telescope Array” for Social Media data – coordinate and aggregate the results of many user’s data collec8on and analysis
• Create open access research papers & findings • Make “collec3ons of connec3ons” easy for users to manage
What we have done: Open Tools
• NodeXL • Data providers (“spigots”) – ThreadMill Message Board – Exchange Enterprise Email – Voson Hyperlink – SharePoint – Facebook – Twi:er – YouTube – Flickr
What we have done: Open Data • NodeXLGraphGallery.org – User generated collec8on of network graphs, datasets and annota8ons
– Collec8ve repository for the research community
– Published collec8ons of data from a range of social media data sources to help students and researchers connect with data of interest and relevance
What we have done: Open Scholarship
What we have done: Open Scholarship
Social Media Research Founda8on h3p://smrfounda:on.org
Heather has high
betweenness
NodeXL Network Overview Discovery and ExploraGon add-‐in for Excel 2007/2010
A minimal network can illustrate the ways different
loca8ons have different values for centrality and degree
Now Available
h:p://www.flickr.com/photos/marc_smith/sets/72157622437066929/
h:p://www.connectedac8on.net/2010/04/25/bernie-‐hogans-‐facebook-‐social-‐network-‐data-‐provider-‐and-‐visualiza8on-‐toolkit/
Network of connec8ons among the people who tweeted the term “PAWCON” on 19 October 2011
NodeXL data import sources
Example NodeXL data importer for Twi:er
NodeXL imports “edges” from social media data sources
NodeXL Automa8on makes analysis simple and fast
NodeXL Network Metrics
NodeXL simplifies mapping data a:ributes to display a:ributes
NodeXL Generates “Sub-‐Graph” Images
NodeXL displays subgraph images along with network metadata
NodeXL allows for fine control over the display of the network
NodeXL Generates Images of Networks
NodeXL Generates Network Graph Images
NodeXL enables filtering of networks
NodeXL Generates Filtered Network Images
Analogy: Clusters Are Occluded Hard to count nodes, clusters
Separate Clusters Are More Comprehensible
TwiDer Network for “MicrosoE Research”
NodeXL Generates Overall Network Metrics
Social networks in TwiDer among people with at least one connecGon to someone else who Tweeted “Obama” on January 25, 2011
Network of word pairs frequently men8ons among people who Tweeted the name “Obama” on January 25, 2011
US Congressman Paul Ryan word network (January 22, 2011)
Congresswoman Michel Bachmann keyword network (January 25, 2011)
What we want to do: (Build the tools to) map the social web • Move NodeXL to the web:
– Node for Google Doc Spreadsheets! – WebGL Canvas
• Connect to more data sources of interest: – RDF, MediaWikis, Gmail, NYT, Cita8on Networks
• Solve hard network manipula8on UI problems: – Modal transform, Time series, Automated layouts
• Grow and maintain archives of social media network data sets for research use.
• Improve network science educa8on: – Workshops on social media network analysis – Live lectures and presenta8ons – Videos and training materials
Work Items Autofill Group A:ribute Merge Edges by A:ribute Modal Transform Merge Workbooks Automated Dynamic Filters: Time Series Analysis, contrast Cap8ons and Legends Upload to Graph Gallery++: cap8ons, workbook Graph Gallery++
User Accounts, Repor8ng, RSS Feeds, Network Visualiza8on Web Canvas
Import: RDF, Wiki, SharePoint, Keyword networks from text Metrics: Triad Census Layouts:
Force Atlas 2, Lin Log, “Bakshy Plots”, Quality Measures Query-‐by-‐example search for network structures
How you can help
• Sponsor a feature • Sponsor Webshop 2012 • Sponsor a student • Schedule training • Sponsor the founda8on • Donate your money, code, computa8on, storage, bandwidth, data or employee’s 8me
• Help promote the work of the Social Media Research Founda8on
Contact:
Marc A. Smith Chief Social Scien8st Connected Ac8on Consul8ng Group [email protected] h:p://www.connectedac8on.net h:p://www.codeplex.com/nodexl h:p://www.twi:er.com/marc_smith h:p://delicious.com/marc_smith/Paper h:p://www.flickr.com/photos/marc_smith h:p://www.facebook.com/marc.smith.sociologist h:p://www.linkedin.com/in/marcasmith h:p://www.slideshare.net/Marc_A_Smith h:p://www.smrfounda8on.org
A project from the Social Media Research Founda8on: h:p://www.smrfounda8on.org
Network Maps for End Users:
Collect, Analyze, Visualize and Communicate
Network Insights with Zero Coding