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Approachable Network AnalysisJeff Horon
Gartner’s Hype Cycle
Source: http://en.wikipedia.org/wiki/File:Gartner_Hype_Cycle.svg
My Mission – Short Circuit the Hype Cycle
Source: http://en.wikipedia.org/wiki/File:Gartner_Hype_Cycle.svg
You will leave here with the knowledge skillsYou will leave here with the knowledge, skills, resources, motivation,
and ideas you need to
d t k l ido network analysis todaytoday
with data you probablywith data you probably
already have
[Social] Network Analysis
So like Facebook? Sort ofSo, like Facebook? Sort of.
B t t k hBut networks are everywhere.
And they aren’t necessarily “social.”
TopicsTopics
Networks 101Networks 101Your Use CasesT f i Y D tTransforming Your DataFree, User-Friendly SoftwareExamplesQ&AQ&A
Networks 101Networks 101
Building BlocksBuilding BlocksPutting the Pieces Together – VisualizationM t iMetrics
Building Blocks
Nodes [Vertices] – People Things IdeasNodes [Vertices] People, Things, Ideas
Links [Edges] – Relationships
or
Visualization
Metrics – Degree
HighestHighestDegree
Metrics – Degree – In-Degree
HighestgIn-Degree“Popular”Popular
Metrics – Degree – Out-DegreeHighest Out-Degree“Gregarious”g
Metrics – Betweenness
HighestHighestBetweenness“Bridge”“Commonalities”
Metrics – Betweenness
Metrics – Closeness
HighestHighestCloseness“Who could spread a rumor?”
Metrics – Closeness
Metrics – Eigenvector Centrality
HighestHighestEigenvector CentralityCentrality“Importance”
Metrics – Eigenvector Centrality
RecapD ( di d) N b fDegree (undirected): Number of
connections
In- / Out-Degree (directed): “Popular” / “G i ”“Gregarious”
Betweenness: “Bridges” / “Commonalities”
Closeness: “Rumor starting point”
Eigenvector Centrality: “Importance”
Your Use Cases – Connect:
People to Other PeoplePeople to Other People
Things/Ideas to Other Things/Ideas
People to Things/Ideas
If the other attendees are starting to look like this to you…like this to you…
Transforming Your DataTransforming Your Data
Common Network Data StructuresCommon Network Data StructuresRelational DatabaseU t t d T tUnstructured Text
Edge List
A list of edges (links)!
A BA CB CB C
Edge List
A list of edges (links)!
A B A BA C A CB C B CB C B C
Edge List
A list of edges (links)!
A B A BA C A CB C B CB C B C
AA
B C
Data You May Already HaveData You May Already Have
Faculty/Staff and Appointing DepartmentsFaculty/Staff and Appointing DepartmentsFaculty/Staff and GroupsP i i l I ti t d S dPrincipal Investigators and Sponsored
ProjectsSponsored Projects and ParticipantsAuthors and Publications
Adjacency Matrix
A table of each node by each node
A B C DA| x 1 1 0 AB| 1 x 1 0B| 1 x 1 0C| 1 1 x 0 B CD| 0 0 0D| 0 0 0 x
D
Transforming Relational Database Data
Where your data has unique identifiers and features associated with them such as:features associated with them, such as:
Transforming Relational Database Data
Join two instances of your table by the unique identifier:unique identifier:
Transforming Relational Database Data
Query for both instances of the feature, returning:returning:
Transforming Relational Database DataNetwork analysis software will remove “self-loops”
and duplicate edges:g
Transforming Relational Database Data
And the resulting visualization might look like:like:
Unstructured Text
Node: Word or phraseLink: Co-occurrence within a block of textLink: Co-occurrence within a block of text
Suppose we wanted to find co occurrencesSuppose we wanted to find co-occurrences among words in unstructured text and words of interest included “network” andwords of interest included network and “text.”
You can construct a network based upon word co-occurrence in unstructured textword co-occurrence in unstructured text.
Unstructured TextYou can construct a network based upon
word co-occurrence in unstructured text.
Edge ListEdge List
network texttext network
Free, User-Friendly Software
NodeXL [http://nodexl.codeplex.com/][ p p ]
-Microsoft Research / University CollaboratorsMicrosoft Research / University Collaborators
-Installs as an Excel 2007 Template-Installs as an Excel 2007 Template
Free easy and powerful with top notch-Free, easy, and powerful with top-notch visualization
Free, User-Friendly Software
Simple Text/Network Mining p g
-Homegrown Excel/Visual Basic Package-Homegrown Excel/Visual Basic Package
-Tech Transfer [http://techfinder.techtransfer.umich.edu/ -Search for # 4730]
LiveLiveDemoDemo
Specific Examples
Things/Ideas and Other Things/Ideas
Concepts and Other Concepts inConcepts and Other Concepts in Publications and Sponsored Project Proposal / Award DataProposal / Award Data
Concepts and Other Concepts in Publications and Sponsored Project Proposal / Award Data
C tConceptIncreasing Betweenness Centrality
Specific ExamplesSpecific Examples
People and Things/IdeasPeople and Things/Ideas
People and Sponsored Projects
Authors and Publication ConceptsAuthors and Publication Concepts
People and Sponsored ProjectsMedical School PI Engineering PIMedical School Project Engineering Project
Specific ExamplesSpecific Examples
People and Other PeoplePeople and Other People
Co-Participation on Sponsored Projects,Co-Authorship
Co-Participation on Sponsored Projects, Co-AuthorshipResearcher / Author Active Project + PublicationI i Ei t C t lit A ti P j tIncreasing Eigenvector Centrality Active Project
Publication
Strategies for CommunicationStrategies for Communication
VisualizationVisualization-Pay attention to node layoutS btl d h d t-Subtly encode as much data as you can
-Include a really simple key
You understand the network dataYou understand the network data, visualization, and metrics + your audience doesn’t = hand deliverdoesn t hand deliver
Q&A
ResourcesResourceshttp://nodexl.codeplex.com/ p p
http://www.umich.edu/~jhoron
Tech Transfer # 4730
On Campus: School of Information, Center for Positive Organizational ScholarshipPositive Organizational Scholarship, Interdisciplinary Group for Research on Innovation