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As part of the LSS@Social Media Week event, Dr. Bernie Hogan took the opportunity to explore what science can show us about Social Networks
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Rebuilding the Collapsed Contexts in Social Media
Bernie Hogan, PhDResearch Fellow, Oxford Internet Institute
University of Oxford
Local Social @ Social Media Week, February 4, 2010
1Saturday, February 6, 2010
The particular case of a peculiar age
Person-to-person networking does not undermine distance. But it makes distance secondary to specific
social relationships. Each individual has their own unique relationships. Like a thumbprint.
We live in an age of access. To be local is to be accessible.
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The paradox of convenienceEveryone is somewhere, no one is everywhere
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Because you can never have too many irrelevant friends
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A social utility?
Source: http://www.alexa.com/topsites5Saturday, February 6, 2010
Source: http://upload.wikimedia.org/wikipedia/en/2/28/Facebook2007.jpg6Saturday, February 6, 2010
What is Facebook? Really?
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Reasons for friends on SNS1. Actual friends 2. Acquaintances, family members, colleagues 3. It would be socially inappropriate to say no because you know them 4. Having lots of Friends makes you look popular 5. It’s a way of indicating that you are a fan (of that person, band, etc.) 6. Your list of Friends reveals who you are 7. Their Profile is cool so being Friends makes you look cool 8. Collecting Friends lets you see more people (Friendster) 9. It’s the only way to see a private Profile (MySpace) 10. Being Friends lets you see someone’s bulletins and their Friends-only blog
posts (MySpace) 11. You want them to see your bulletins, private Profile, private blog (MySpace) 12. You can use your Friends list to find someone later 13. It’s easier to say yes than no.
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The friend numbers game
•Large university in the American Midwest.
•First year social statistics class (2009)
•95% Response Rate
•Data captured through Facebook API
•N = 393.
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Too Many Friends!
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And too many connections
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But again, scale matters.
Men with 500 friends only have mutual conversations with 10 of them. Its up to 16 for women.
That’s less than 4% of friends.
Source: Economist (via Overstated.net)
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ocial Network Analysis to the Rescue!
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Trace data can tell a lot
Source: Predicting tie strength with social media. Eric Gilbert, Karrie Karahalios and Christian Sandvig.
CHI ’09
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Friend listsTedious and incoherent
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Eigenvector CommunityWell partitioned, but
overwhelming
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Greedy CommunityLarge swaths of Sense
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Friends from Undergraduate (15%)
Professional Colleagues (23%)
High SchoolFriends (24%)
Family (8%)
Intern friends (3%)
Single event friends (3%)
Current Co-workers (13.4%)
Summer Camp Friends (2%)
Grad School Colleagues and Friends (12%)
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Network as Context in Email
Source: Hansen, D. (forthcoming) Analyzing Social Media with NodeXL, chapter 8.22Saturday, February 6, 2010
Network as context in Twitter
Source: Smith, M. (forthcoming) Analyzing Social Media with NodeXL, chapter 4.23Saturday, February 6, 2010
Networks in Twitter II
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So what?
• Lurking within any social network site profile is a host of clustered peers. Discovering these groups through community detection is an effective way to bring coherence to a profile, and help it scale.
• Consider: planning a party, recommending a concert, sending out important news.
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Nearness is now a social property as
much as a spatial one.This is not the same thing as collaborative
filtering. Networks do not signify similarity, they signify community. These are the people that do things together,
disclose information to each other.
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Looking forwardParticular relationships create networks.
Norms of access create overload.
Thinking local is one solution, but it is partial.
We need to create contexts, so users don’t have to.
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Thank YouBernie Hogan
Research Fellow, OII@blurky
;)
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