Leveraging NodeXLfor Visualizationof Social Network Data

Visualizing Social Data with Twitter, MapBox, and NodeXL

C. Scott Dempwolf, PhDResearch Assistant Professor& Director

Social Data and Analytics MeetupThe Washington Post

August 19, , 2014

UMD – Morgan StateCenter for Economic Development

Who are you ?(and why are you staring at me?)

Who you were yesterday… Who you are today…

Who am I?(and how did I get here?)

• At UMD since 2007– 2007 – 1012 PhD student– 2012 - Research Asst.

Professor

• Using NodeXL since 2011• Uses of Social Network

Analysis in Planning• Focus on innovation &

economic development

Social Network TheoryIn one slide

• Central tenet – Social structure emerges from – the aggregate of relationships (ties) – among members of a population

• Phenomena of interest– Emergence of cliques and clusters – from patterns of relationships– Centrality (core), periphery (isolates), – betweenness

• Methods– Surveys, interviews, observations,

log file analysis, computational analysis of matrices

(Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001)http://en.wikipedia.org/wiki/Social_network

Source: Richards, W. (1986). The NEGOPY network analysis program. Burnaby, BC: Department of Communication, Simon Fraser University. pp.7-16

OK… two slides

• Node– “actor” on which relationships act; 1-mode versus 2-mode networks

• Edge– Relationship connecting nodes; can be directional

• Cohesive Sub-Group– Well-connected group; clique; cluster

• Key Metrics– Centrality (group or individual measure)

• Number of direct connections that individuals have with others in the group (usually look at incoming connections 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 connections 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

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Why I Use NodeXL

Built on ExcelEasy to learnUser friendlyFlexibleFREE*Community of users

Using NodeXL to AnalyzeInnovation Networks

Using NodeXL to AnalyzeInnovation Networks

Visualizing CrunchBase Data

Global Capital FlowsAccelerators, Investors & Startups

Why networks & technology matter

• Startups need to be seeded into strong clusters

• Clusters have strong connections to markets, supply chains and talent pools

• Clusters form around technologies

• Capital flows around technologies

What about social media?

6 Kinds of Twitter Networks

Cool pictures but so what?

Th

e n

etw

ork

you h

ave

The network you want

What Now?

Contemplate your hashtags Get started with NodeXL

Thanks to Marc Smith for letting me cannibalize his slides