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Analyzing Social Media Networks with NodeXL Derek L. Hansen [email protected] AAHB Workshop

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Analyzing Social Media Networks with NodeXL

Derek L. Hansen

[email protected]

AAHB Workshop

Center for the Advanced Study

of Communities and Information

Human-Computer

Interaction Lab

What is Social Media?

A set of networked technologies that supports social interactions.

Social media is about “transforming monologue (one-to-many) into dialog (many-to-many).”1

1 www.webpronews.com/blogtalk/2007/06/29/the-definition-of-social-media

Types of Social MediaAsynchronous

Threaded Conversation

Email, Google groups, Yahoo Answers, Listservs, Stack

Overflow

Synchronous Threaded

Conversation

Instant Messaging, IRC, Skype, Google Hangouts

Collaborative Authoring Wikipedia, Wikia, Google Docs

Blogs & Podcasts Livejournal, Blogger, Twitter, Vlogs, podcasts, photo blogs

Social Sharing YouTube, Flickr, Instagram, Pinterest, Last.Fm, Delicious,

Reddit, Snapchat

Social Networking Facebook, LinkedIn, eHarmony, Ning, Ravelry

Online Markets &

Production

eBay, Amazon, craigslist, Kiva, Thraedless, TopCoder,

ePinions, Yelp

Idea Generation IdeaConnection, IdeaScale

Virtual Worlds Webkinz, World of Warcraft, Club Penguin, Second Life

Mobile-based Services Foursquare, MapMyRun, Geocaching

Patterns are left behind

Online Community Analysis

• 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)

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

Social Network Theoryhttp://en.wikipedia.org/wiki/Social_network

SNA 101• 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

E

D

F

A

CB

H

G

I

CD

E

A B D E

Social Network AnalysisA systematic method for understanding relationships

between entities.

Node-Specific Metrics

• Betweenness Centrality

• Degree Centrality

• Eigenvector Centrality

• Closeness Centrality

Network-Specific Metrics

• Components

• Density

Personal Email Collection

Mapping Corporate Email Communication Between Research Groups

Mapping Events with Twitter EventGraphs

Who is Talking about Thimerosal on Twitter?

6 kinds of Twitter social media networks

[Divided]Polarized Crowds

[Unified]Tight Crowd

[Fragmented]Brand Clusters

[Clustered]Community Clusters

[In-Hub & Spoke]Broadcast Network

[Out-Hub & Spoke]Support Network

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 setters

Discussion people, Topic setters

Inferring Relationships

Surgery Videos on YouTube

Finding Theorists in Lostpedia

NodeXL (http://nodexl.codeplex.com)

Social Media Research FoundationPeople Disciplines Institutions

University Faculty Computer ScienceInformation Technology

University of MarylandBrigham Young University

Students HCI, CSCW Oxford Internet Institute

Industry Machine Learning Stanford University

Independent Information Visualization Microsoft Research

Researchers UI/UX Illinois Institute of Technology

Developers Social Science/Sociology Connected Action

Network Analysis Cornell

Collective Action Morningside Analytics

http://nodexl.codeplex.com

NodeXLGraph Gallery

An Iterative Process

Data Sources Code it Yourself

Use Free 3rd Party Tools

APIs

Scrapers

Software

Libraries

Use Corporate Tools