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Analyzing Social Media Networks with NodeXL Derek L. Hansen Maryland’s iSchool

NodeXL Research

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This is a presentation that describes at a high level some of the work we've been performing related to NodeXL and it's use to understand social media networks.

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Analyzing Social Media Networks with NodeXL

Derek L. HansenMaryland’s iSchool

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Patterns are left behind

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Research GoalDevelop powerful tools, processes, and methods that dramatically lower the barriers for community managers and researchers to make sense of social media interactions.

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Online Community Analysis

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Social Network AnalysisA systematic method for understanding relationships between entities.

Vertex-Specific Metrics• Betweenness Centrality• Degree Centrality• Eigenvector Centrality• Closeness Centrality

Network-Specific Metrics• Components• Density

Clusters & Subgroups• Grouped based on

shared connections

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Research Question (1)• How can the complex, sophisticated set of

SNA techniques be supported in an intuitive manner for community analysts?

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

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Lesson’s Learned+ Tight integration of spreadsheet & visualization

+ Attribute data and SNA metrics can be mapped onto rich set of visual properties

+ Data importers

+ Dynamic filters

- Not platform independent or web-based- Lack of “undo”- Poor at dealing with multiple networks

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Research Questions (2)• How do non-technical

users learn SNA and apply it to understand community interaction?

• What barriers do they encounter?

• How should SNA tools be customized for novices?

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Novice SNA Study• Participants: 16 grad students in course on Online

Communities• Task: create insightful network visualization &

explanation of online community they’d been studying (3 weeks with feedback from peers & instructor)

• Data collection: diaries, observations, interviews, questionnaire, content analysis of assignments, in-class process recap

• Data analysis: grounded theory approach• Output: process model; challenges; supports

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Mapping Sub-Groups of Ravelry

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Finding an Alternate Admin

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Inferring Relationships

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Challenges & Supports

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What Novices Need…• Social media “network” data importers• Better defined & recognized network

visualization “genres”• Improved layout algorithms• The ability to share visualizations & analysis• Basic network literacy

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Research Questions (3)• How can SNA be applied to different social

media platforms to gain actionable insights?• What network “genres” lead to actionable

insights?

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Personal Email Collection

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Mapping Corporate Email Communication Between Research Groups

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Surgery Videos on YouTube

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Finding Friendship Clusters in Facebook

By Bernie Hogan

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Finding Theorists in Lostpedia

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Mapping Events with Twitter EventGraphs

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ConclusionThere is a pressing need to support community managers and researchers trying to make sense of social media data – especially relational data.

Novices benefit from tight data/visualization coupling, example visualizations, data importers, good network layouts, and collaboration even from other novices.

Researchers and practitioners could benefit from a pallet of network visualization “genres” for specific social media networks, which can be used to gain actionable insights.

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The Future of Social Media Networks

• Networks and place• Networks over time• Comparing multiple networks• Bi-modal, multiplex, affiliation and other

non-standard networks• Improved relational data spigots

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Reflections for Social Media Researchers

• Don’t get bogged down in endless data exploration

• Network analysis is ideally coupled with qualitative methods

• Remove unnecessary elements of visualizations so it clearly tells your story

• Work with real-world clients, not just academically “interesting” work

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Analyzing Social Media Networks with NodeXL

Derek L. Hansen

Thanks to Microsoft Research• Natasa Milic-Frayling

• Dan Fay

Collabortors:• Ben Shneiderman

• Marc Smith • Dana Rotman

• Elizabeth Bonsignore•

The NodeXL Team

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Ask me about…• Alternate Reality Games (ARGs) in the service of

education and design• BioTracker – a mobile-based game designed to

capture multimedia data about rare species for the Encyclopedia of Life

• Fact Check: HPV – a Facebook app that tests a novel design to disseminate info on stigmatized illnesses

• Using Twitter data to map the political bias of news outlet audiences

• Supporting local community action in Alexandria, Virginia with ACTion Alexandria