Is that good?
Can Social Network Analysis Inform Community Management
Paul Pedrazzi
Vice President, Product Strategy, Oracle.
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A Tale of Two Networks
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
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A Simple Question...
...is that good?
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image credit: Amber in Norfolk
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image credit: David C. Foster
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What makes...
...a network healthy?
and how do you diagnose and influence it
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20
200
E 1
20
100
F P 2
20
70
T O Z 3
20
50
LPED 4
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40 PECFD 5
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30 E D F C Z P 6
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25 F E L O P Z D 7
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20 D E F P O T E C 8
9
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15 L E F O D P C T
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10 F D P L T C E O 10
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5 P E S O L E F T D 11
photo credit: skyfaller
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Diagnosis
Hubs: Connected to the most people.
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Diagnosis
Hubs: Connected to the most people.
Gatekeepers: Control access to the disconnected.
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Diagnosis
Hubs: Connected to the most people.
Gatekeepers: Control access to the disconnected.
Monitors: Close(<3d) to the most people.
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Diagnosis
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.
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Diagnosis
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.
Bridges: Span two communities.
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Ok, but...
...what is the treatment?
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It depends...
...on the patient (objectives)
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Treatments (Experimental)
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.
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Treatments (Experimental)
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.
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Treatments (Experimental)
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.
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Treatments (Experimental)
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.
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Treatments (Experimental)
Objective:
“To increase the flow of information to everyone.”
Challenge:
“Finding the bottlenecks and the isolated members”
Hypothesis:
Identify and circumvent the gatekeepers.
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Treatments (Experimental)
Objective:
“To increase the members feeling of belonging.”
Challenge:
“Shorten the paths between individuals (focus <3)”
Hypothesis:
Measure the paths and create more monitors.
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Summary
Our measurement model is broken.
Understanding social networks is mature in academia.
Analysis can help community managers prioritize their efforts.
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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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