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Real-World Social Networks: Structure and Dynamics Bottom Up

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Presentation on theme: "Real-World Social Networks: Structure and Dynamics Bottom Up"— Presentation transcript:

1 Real-World Social Networks: Structure and Dynamics Bottom Up
Robin Dunbar Institute of Cognitive & Evolutionary Anthropology University of Oxford

2 The Global Village? The Internet was based on the promise of enlarging your social world beyond the limits of the local village But does it actually work?

3 Does Technology Really Widen Your Horizons?
The answer from Facebook’s own data seems to be: No Modal number of friends is You may list 100s of friends, but you only talk to a few WHY? Cameron Marlow web-blog 3

4 To Begin at the Beginning….
Social Brain Hypothesis Among primates, social group size is determined by neocortex volume Predicted group size for humans is ~150 [Dunbar’s Number] Monkeys Apes Dunbar (1992, 1993)

5 These all have mean sizes of 100-200
Twitter exchange contacts Human Social Networks Gonçalves et al. (2011) Killworth et al (1984)) Her 152 facebook friends ….remembered forever These all have mean sizes of Neolithic villages 6500 BC military units (company) (N=10) 180 * Hutterite communities (N=51) 107 Nebraska Amish parishes (N=8) 113 business organisation <200 ideal church congregations <200 Doomsday Book villages C18th English villages * GoreTex Inc’s structure Research sub-disciplines (N=13) Twitter personalised contacts Small world experiments (N=2) 134 Hunter-Gatherer communities Xmas card networks “Reverse” Small World Experiments 100 10 Hunter-Gatherer Societies Dunbar (1993) Individual Tribes SusyJ87 Hill & Dunbar (2003) Xmas Card Networks Dunbar (1993, 2008) 5

6 BUT….Human Networks are NOT Homogenous
Less like this …..and more like this

7 Intimacy, Frequency and Trust
Contact frequency differs across layers There is a relationship between frequency of contact and intimacy Hill & Dunbar (2003) 7

8 The Fractal Periodicity of Human Group Sizes
Sizes of Hunter-Gatherer Groupings Peak at =5.4 Slope  3 Social Groupings Database [N=60] Hamilton et al (2007) Peak at =5.2 Xmas Card Database Scaling ratio = exp(2π/) = 3.2 and 3.3 Zhou, Sornette, Hill & Dunbar (2005)

9 The Friendship Shells Our social worlds consist of layers of relationships …with 150 as the core number ….and a scaling ratio of ~3 …but extending beyond to 500, 1500 Intensity EGO 5 15 50 150 1500 500

10 Intimacy, Frequency and Trust
Mean contact frequency/day Mean Emotional Closeness Network Layer Sutcliffe et al (in press) Contact frequency and emotional closeness differs across layers The layers appear to be quite discrete 10

11 Network Structure Has Consequences
Happy Intermediate Unhappy Fowler et al (2008) Christakis (2007) Happiness and obesity are contagious …with effects up to three degrees away

12 Network Density is Important
How well integrated your close network is influences your willingness to act altruistically Estimates of Fixed Effectsa Parameter Estimate Std. Error df t Sig. Intercept 2.35 0.60 321.59 3.92 0.00 AGREEABLENESS 0.07 0.05 283.66 1.47 0.14 CONSCIENTIOUSNESS -0.09 0.06 281.99 -1.54 0.12 YEARS_KNOWN 0.03 9.81 CONTACT_FREQUENCY 0.34 0.02 13.88 AGREEABLENESS of TARGET 0.09 0.01 7.34 CONSCIENTIOUSNESS of TARGET 7.76 NETWORK DENSITY 2.79 Would you lend £5000? Curry & Dunbar (in press)

13 The Circles of Acquaintanceship
Our networks are structured by more than just social closeness Intensity EGO Our networks are also split roughly equally between Family (kin) and Friends – two separate sub-networks that intersect FRIENDS 5 FAMILY 15 50 150 500

14 The Kinship Factor Our networks consist of about 50% kin [family]
80 close networks Inner layers Outer layers Slope  -1 Our networks consist of about 50% kin [family] Kin are given priority over Friends If you come from a large extended family, you have fewer friends! 250 complete networks -0.3 < slope< -0.9 Total Kin

15 Blood is Thicker Than Water
How much I value you relative to myself We value kin more than we value friends ….. in any given layer of the network Welfare Trade-off Ratio Family Friends Network Layer Curry & Dunbar (in press)

16 Stable Family, Fragile Friends
Stay KIN Move Friends Change in Network Layer Change over Time months Kin Friends Roberts & Dunbar (2011)

17 by change in activity score by change in contact frequency
How to Prevent Relationships Decaying Change in Emotional Closeness months 0-9 This is for friends only. Contact frequency here is based on self-report data, as I am still processing the detailed data from the phone bills. First graph – shows how change in emotional closeness is affected by change in the number of activities that ego and alter do together. So either decrease in activities from month 1 to month 9, no change, or doing more activities at month 9 than at beginning of study. For females, doesn’t seem to make much difference – decline in emotional closeness regardless of activities done together. For males, to offset decay in emotional closeness, physically doing things together seems to work well. This is the same graph for contact frequency – this includes both face-to-face and non face-to-face contact. So have decrease in contact frequency from month 1 to month 9, no change, or increase in frequency of communication from month 1 to month 9. For here, for females, it seems that to increase emotional closeness, communication rather than shared activities is the key, whereas for men, not such a strong effect of contact frequency. Supports previous research in this area – men’s friendships based around shared activities, whereas women's friendships based around communication and emotional intimacy. The advantage of this study is that we can look at how things like shared activities and communication dynamically affect relationships over the course of 18 months, and have very fine-grained data on communication patterns from the mobile bills. Roberts & Dunbar (2010) by change in activity score by change in contact frequency 17 17

18 What Makes Relationships Work?
Primate social bonds seem to involve two distinct components: An emotionally intense component [=grooming] A cognitive component [=brain size + cognition]

19 The Limits to Intentionality...
% Correct A natural limit at 5th order intentionality: “I intend that you believe that Fred understands that we want him to be willing to [do something]…” [level 5] Intentionality Level

20 The Cognitive Limits to Sociality
The Orders [or Levels] of Intentionality 5th order seems to be the limit “I intend that you believe that Fred understands that we want him to be willing to [do something]…” Intentionality correlates with size of support clique Stiller & Dunbar (2007) Powell et al (2010)

21 Insights from Neuroimaging
Powell et al (2010 & in press) In a stereological analysis of gross volume: best predictor of network size and intentional competence is orbitofrontal PFC volume In a fine-grained VBM (voxel) analysis: overlap of network size and intentional competence in the orbitovental PFC Lewis et al (in press) 21 21

22 How Grooming Works endorphins are relaxing
An experimental study with monkeys Opiates block social drive; Opiate-blockers enhance social drive Sal endorphins are relaxing They create a psycho-pharmacological environment for building trust?

23 Grooming Time in Humans?
If we bonded our groups using the standard primate mechanism ….we would have to spend 43% of the day grooming

24 Grooming Time in Humnas?
In fact, we spend only 20% of our time in social interaction …..from a sample of 7 societies from Dundee to New Guinea How do we bond our super-large communities?

25 Laughter as Virtual Touch?
Change in Pain Threshold in Response to Laughter Factual vs Comedy Videos Pain threshold as an assay for endorphin activation Laughter as a form of virtual grooming to bond more individuals? Comedy EdinburghFringe Edinburgh Fringe Neutral Procedure: pain test video/activity pain re-test Dunbar et al (submitted)

26 Nothing Beats Reality….?
Both perceived happiness AND laughter rates, F2F and Skype are better than all other media Laughter influences happiness [except in Skype] And may be more important than duration of interaction in promoting satisfaction Satisfaction Rating Frequency of Laughter Satisfaction Rating Vladovik et al (submitted) NO YES Laughter

27 Synchony Ramps up the Endorphins
Change in pain threshold before and after 45 mins rowing work-out on ergometers in the gym: Alone vs in a virtual boat Alone Group Alone Group

28 With Thanks to…. Funding: British Academy EPSRC ESRC Leverhulme Trust
Comparative brains: Dr Susanne Shultz Social Networks and behaviour: Dr Sam Roberts Dr Tom Pollet Dr Oliver Curry Dr Holly Arrow Dr Jens Binder Prof Alistair Sutcliffe Tatiana Vlahovic Dr Wei Zhou Dr Russell Hill Prof Didier Sornette Prof Mark van Vugt Rebecca Baron, Ellie Pearce and Anna Frangou Neuroimaging: Amy Birch Joanne Powell Rachel Browne Dr Penny Lewis Prof Neil Roberts Dr Marta García-Fiñana Funding: British Academy EPSRC ESRC Leverhulme Trust EU-FP7

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