defrag 08: is that good?
TRANSCRIPT
Is that good?Can Social Network Analysis Inform Community Management
Paul PedrazziVice President, Product Strategy, Oracle.
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A Tale of Two Networks
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Mix Connect
Total Users 28,841 80,000
PageViews (monthly) 142,220 58,775
Unique Visits (monthly) 15,525 3,732
Sharing Activity (avg/user/month) 0.45 0.67
Connections (avg) 4.92 6.18
A Simple Question...
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...is that good?
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image credit: Amber in Norfolk
image credit: David C. Foster
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What makes...
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...a network healthy?and how do you diagnose and influence it
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EF PT O ZL P E DP E C F DE D F C Z P
F E L O P Z D
D E F P O T E C
L E F O D P C TF D P L T C E OP E S O L E F T D
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photo credit: skyfaller
Diagnosis
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Hubs: Connected to the most people.
Diagnosis
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Hubs: Connected to the most people.
Gatekeepers: Control access to the disconnected.
Diagnosis
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Hubs: Connected to the most people.
Gatekeepers: Control access to the disconnected.
Monitors: Close(<3d) to the most people.
Diagnosis
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Hubs: Connected to the most people.
Gatekeepers: Control access to the disconnected.
Monitors: Close(<3d) to the most people.
Loners: Not connected within this network.
Diagnosis
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Hubs: Connected to the most people.
Gatekeepers: Control access to the disconnected.
Monitors: Close(<3d) to the most people.
Bridges: Span two communities.
Loners: Not connected within this network.
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Ok, but...
...what is the treatment?
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It depends...
...on the patient (objectives)
Treatments (Experimental)
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Objective: “Ensure my community is doing the right things for its members”
Challenge: “Who do you ask for the best perspective?”
Hypothesis: Reach out to the monitors as those most tapped in.
Treatments (Experimental)
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Objective: “How can we get the best ideas out in the open?”
Challenge: “Finding the innovators amongst the crowd.”
Hypothesis: Entice bridges to join the conversations.
Treatments (Experimental)
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Objective: “Bring in different voices to stimulate new conversations.”
Challenge: “How can you tap the diversity beyond your network clique?”
Hypothesis: Encourage loners to invite externally.
Treatments (Experimental)
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Objective: “To increase the durability of our community.”
Challenge: “Where is it strong and where is it weak?”
Hypothesis: Create more hubs to minimize the points of failure.
Treatments (Experimental)
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Objective: “To increase the flow of information to everyone.”
Challenge: “Finding the bottlenecks and the isolated members”
Hypothesis: Identify and circumvent the gatekeepers.
Treatments (Experimental)
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Objective: “To increase the members feeling of belonging.”
Challenge: “Shorten the paths between individuals (focus <3)”
Hypothesis: Measure the paths and create more monitors.
Summary
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Our measurement model is broken.
Understanding social networks is mature in academia.
Analysis can help community managers prioritize their efforts.
References
Dekker, Anthony, “Conceptual Distance in Social Network Analysis”, JoSS Volume 6,http://www.cmu.edu/joss/content/articles/volume6/dekker/
Freeman, Linton (1979) “Centrality in Social Networks: I. Conceptual Clarification,” Social Networks 1:215-239
Krackhardt, David, Assessing the Political Landscape: Structure, Cognition, and Power in Organizations, Administrative Science Quarterly, 35 (1990): 342-369
Krebs, Valdis “Social Networking Analysis a Brief Introduction” http://www.orgnet.com/sna.html
McCarty, Christopher, “Structure in Personal Networks”, JoSS 3, http://www.cmu.edu/joss/content/articles/volume3/McCarty.html
McGrath, Kathleen and Krackhardt, David (2003) “Network Conditions for Organizational Change”, Journal of Applied Behavioral Science, Vol.39, No.3:324-336
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Q A&
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