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A project from the Social Media Research Founda8on: h:p://www.smrfounda8on.org
Crowd Photography
for Social Media
Social Media Research Founda8on h"p://smrfounda/on.org
Social Media Research Founda8on People Disciplines Ins-tu-ons
University Faculty
Computer Science University of Maryland
Students HCI, CSCW Oxford Internet Ins8tute
Industry Machine Learning Stanford University
Independent Informa8on Visualiza8on
MicrosoM Research
Researchers UI/UX Illinois Ins8tute of Technology
Developers Social Science/Sociology Connected Ac8on
Network Analysis Cornell
Collec8ve Ac8on Morningside Analy8cs
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
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
We envision hundreds of NodeXL data collectors around the world collec8vely genera8ng a free and open archive of social media network
snapshots on a wide range of topics.
h:p://msnbcmedia.msn.com/i/msnbc/Components/Photos/071012/071012_telescope_hmed_3p.jpg
Social Media (email, Facebook, Twi:er, YouTube, and more) is all about connec8ons
from people
to people.
12
Pa:erns are leM behind
13
There are many kinds of 8es….
h:p://www.flickr.com/photos/stevendepolo/3254238329
Like, Link, Reply, Rate, Review, Favorite, Friend, Follow, Forward, Edit, Tag, Comment, Check-‐in…
“Think Link” Nodes & Edges
Is related to
A B
Strong -es
Weak -es
Social Networks
• History: from the dawn of 8me!
• Theory and method: 1934 -‐>
• Jacob L. Moreno
• h:p://en.wikipedia.org/wiki/Jacob_L._Moreno Jacob Moreno’s early social network diagram of positive and negative relationships among members of a
football team. Originally published in Moreno, J. L. (1934). Who shall survive? Washington, DC: Nervous and Mental Disease
Publishing Company.
World Wide Web
Each contains one or more social networks
Hubs
Bridges
h:p://www.flickr.com/photos/library_of_congress/3295494976/sizes/o/in/photostream/
h:p://www.flickr.com/photos/amycgx/3119640267/
Introduc8on to NodeXL
Like MSPaint™ for graphs. — the Community
Heather has high
betweenness
NodeXL Network Overview Discovery and Explora-on add-‐in for Excel 2007/2010
A minimal network can illustrate the ways different
loca8ons have different values for centrality and degree
#occupywallstreet 15 November 2011
#teaparty 15 November 2011
h:p://www.newscien8st.com/blogs/onepercent/2011/11/occupy-‐vs-‐tea-‐party-‐what-‐their.html
• 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
D
F
A
C B
H
G
I
C D
E
A B D E
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
h:p://www.flickr.com/photos/marc_smith/sets/72157622437066929/
NodeXL Free/Open Social Network Analysis add-in for Excel 2007/2010 makes graph
theory as easy as a pie chart, with integrated analysis of social media sources. http://nodexl.codeplex.com
Now Available
Communi8es in Cyberspace
Twitter Network for “Microsoft Research” *BEFORE*
Twitter Network for “Microsoft Research” *AFTER*
NodeXL Ribbon in Excel
NodeXL data import sources
Example NodeXL data importer for Twi:er
NodeXL imports “edges” from social media data sources
NodeXL creates a list of “ver8ces” from imported social media edges
NodeXL displays subgraph images along with network metadata
NodeXL Automa8on
makes analysis simple and fast
Perform collec8ons of common
opera8ons with a single click
NodeXL Network Metrics
NodeXL “Autofill columns” simplifies mapping data a:ributes to display a:ributes
NodeXL enables filtering of networks
NodeXL Generates Overall Network Metrics
Social Network Maps Reveal
Key influencers in any topic.
Sub-‐groups.
Bridges.
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
2012 Schedule: Planned Workshops
March 1 -‐ Strata March 5 2012 – PAWCON June 2012 -‐ ICWSM July 2012 – Lipari School on Complexity August 8, 2012 -‐ AEJMC August 21, 2012 – Webshop 2012
Pending 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
Thank you!
The Social Media Research Founda8on
h:p://www.smrfounda8on.org
Backup
• Examples of social media network analysis • Sources of social network analysis material
Who is the mayor of your hashtag?
Find out at: h:p://netbadges.com
Who is the mayor of your hashtag?
Find out at: h"p://netbadges.com
h:p://netbadges.com
Who is the mayor of your hashtag?
Find out at: h"p://netbadges.com
