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Robin Dunbar "Has the Internet Changed Our Social World?"

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Presentation to 26th HBES Workshop Natal, 30 July 2014 - Internet Science official JRA6 workshop.

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Robin Dunbar "Has the Internet Changed Our Social World?"

  1. 1. HHaass tthhee IInntteerrnneett CChhaannggeedd OOuurr SSoocciiaall WWoorrlldd?? Robin Dunbar
  2. 2. The Global Village? The Internet was based on the promise of enlarging your social world beyond the limits of the local village But has it actually worked?
  3. 3. Social Brain Hypothesis • Predicted group size for humans is ~150 • “Dunbar’s Number” Monkeys Apes Neocortex volume divided by rest of brain
  4. 4. The Natural Size of Human Communities? These all have mean sizes of 100-200 Neolithic villages 6500 BC 150-200 Modern armies (company) 180 Hutterite communities 107 ‘Nebraska’ Amish parishes 113 business organisation <200 ideal church congregations <200 Domesday Book villages [1087 AD] 150 C18th English villages 160 GoreTex Inc’s structure 150 Research sub-disciplines 100-200 Small world experiments 134 Hunter-Gatherer communities 148 Xmas card networks 154 225-249 175-199 125-149 75-99 Maximum Network Size 325-349 350-374 275-299 300-324 250-274 200-224 150-174 100-124 25-49 50-74 10000 1000 100 10 0-24 Number of Cases 10 9 8 7 6 5 4 3 2 1 0 1 0 10 20 30 “Reverse” Small World Experiments Hunter-Gatherer Societies Xmas Card Networks Individual Tribes
  5. 5. Human http://www.youtube.com/watch?v=ApOWWb7Mqdo Social Groups These aallll hhaavvee mmeeaann ssiizzeess ooff 110000--220000 Neolithic villages 6500 BC 150-200 Modern armies (company) 180 Hutterite communities 107 ‘Nebraska’ Amish parishes 113 business organisation <200 ideal church congregations <200 Doomsday Book villages 150 C18th English villages 160 GoreTex Inc’s structure 150 Research sub-disciplines 100-200 Small world experiments 134 Hunter-Gatherer communities 148 Xmas card networks 154 225-249 175-199 125-149 75-99 Maximum Network Size 325-349 350-374 275-299 300-324 250-274 200-224 150-174 100-124 25-49 50-74 10000 1000 100 10 0-24 It was an advertising stunt! Number of Cases 10 9 8 7 6 5 4 3 2 1 0 1 0 10 20 30 “Reverse” Small World Experiments Killworth et al (1984) Hunter-Gatherer Societies Dunbar (1993) Luckily, it’s a hoax…. Individual Tribes Xmas Card Networks Her 152 friends recorded for posterity…..? Hill & Dunbar (2003)
  6. 6. Is Your Online Network Bigger than ~150? Twitter Email Gonzalez et al. (2011:PLoS-1) Haeter et al (2012: Phys. Rev. Letts) • Network size estimated from reciprocated exchanges • # edges drops off after ~200
  7. 7. Has Facebook Really Widened Your Social World? • It seems not…. • Modal number of ‘friends’ on Facebook = 150-250 • You may list 100s of friends, but you only talk to a handful N » 1 million Facebook users
  8. 8. BUT….our friends are NOT all the same! Our social world is less like this …..and more like this
  9. 9. Intimacy, Frequency and Trust • Relationship between frequency of contact and intimacy • Trust and obligation seem to be important 0 1 2 3 4 5 6 7 8 9 10 Emotional Mean Time Since Last Contact (Months) 8 6 4 2 0 LOW Emotional Closeness HIGH
  10. 10. The Fractal Periodicity of Human Group Sizes Peak at w=5.4 Peak at w=5.2 Sizes of Hunter-Gatherer Xmas Card Database Social Groupings Database [N=60] Scaling ratio = exp(2π/w) Groupings = 3.2 and 3.3 Zhou, Sornette, Hill & Dunbar (2005) Hamilton et al (2007)
  11. 11. The Expanding Circles Our relationships form a hierarchically inclusive series of circles of increasing size but decreasing intensity [ie quality of relationship] We know all these layers exist …and the military maintain the sequence far beyond [to ~50,000] 5 15 50 150 Intensity EGO 500 1500
  12. 12. The Military Model Modern Army Organisation USA Australia [1994] [2010] The need to solve two conflicting requirements: Section 10 12 Platoon 30 45 Company 126 168 Battalion 650 775 Brigade/Regiment 4000 3750 Division 12,500 15,000 War of Spanish Succession [1701-1714] Maximising cohesion and the number of boots-on-the-ground
  13. 13. Network Structure on Facebook • Facebook regional network in April 2008 • 3M nodes with 23M edges [useable dataset: 92,300 nodes] • Density-based clustering: Optimal cluster structure is 4 layers • Layer sizes correspond exactly to those found by Zhou et al. (2005) in F2F networks ….with a scaling ratio of ~3 ….AND an added layer at 1.5 Optimal Cluster # Support Sympathy Affinity ?? clique group group Cumulative size: 1.6 5.7 17.6 52.2 Predicted size: (1.5) 5 15 50 Arnaboldi et al. (2012)
  14. 14. Network Structure on Twitter • 205,000 human Twitter followers, 200M tweets • Reciprocated postings • Optimal # clusters = 4 • Layers have same scaling ratio [~3) and sizes virtually identical to theoretical layers Facebook: 1.6 5.7 17.6 52.2 Theoretical: 1.5 5 15 50
  15. 15. The Expanding Circles … as they really are • It turns out, as predicted, that there really is an inner-inner layer at 1.5 • …perhaps because girls can have two intimate relationships (a best girlfriend PLUS a boyfriend) ….but boys can only manage one (a girlfriend or nothing)? 5 15 50 150 1.5
  16. 16. Social Bonding Primate-Style Primate social bonds seem to involve two distinct components: An emotionally intense component [= grooming Þ endorphins] A cognitive component [=brain size + cognition]
  17. 17. • Best predictor of network size is orbitofrontal prefrontal cortex volume • In a fine-grained VBM (voxel) analysis: best predictor of network size is ventromedial PFC • 2 of 7 neuroimaging studies showing correlations between brain region volume and network size in humans and macaques Friendship on the Brain?
  18. 18. Importance of Time Change in Emotional Closeness Daily contact rates per person Kin Friends 0 9 18 months Friendships decline rapidly in the absence of contact
  19. 19. Time really is a Network Constraint • Mobile phone dataset from 11 months [20M users and 9 billion calls] • As network size [k] gets larger, o mean call rate asymptotes at ~200 o call diversity declines after a peak at k≈15 Total calling is time is limited, and gets distributed more thinly • There is a natural limit to network size, and it is set [in part] by how thinly social capital can be invested Miritello et al. (2013)
  20. 20. Just how consistent are these patterns? An 18-month longitudinal study of 30 18-year-olds transitioning to University ….for whom we have complete call + text records and detailed relationship questionnaires (at start, mid and end) Roberts et al (2009), Roberts & Dunbar (2010a,b)
  21. 21. Stability of Social Signatures • Alters ranked by frequency of calls • Ranking pattern remains similar across all three 6-mnth windows DESPITE high turnover in in membership in successive 6- month windows [esp. in first interval as indicated by low Jaccard index – indexes similarity] • 25% to top Alter 48% to top 3 Alters Saramaki et al. (2014)
  22. 22. Stability of Social Signatures • Comparison between 3 intervals • Individual signatures are significantly more similar over time [dself] than they are to other individuals’ signatures [dref] • Picture is identical using Emotional Closeness, duration of calls and # texts Saramaki et al. (2014) Ego 1 Ego 2
  23. 23. Three Ways We Solved the Bonding Problem Modern humans Archaic humans -.5 0.0 .5 1.0 1.5 2.0 2.5 3.0 3.5 Millions Years BP Predicted Grooming Time (%) 50 40 30 20 10 Religion and its rituals Music and dance Laughter a cross-cultural trait shared with chimpanzees Australopiths H. erectus
  24. 24. Something in the Way She Moves….? • A study carried out in Brazil with very simple dance moves Change in Pain Threshold Self-in-Other Index
  25. 25. Conclusions • Human social networks are constrained by (1) cognition and (2) time • The internet has increased the distance over which we can contact network members…. • BUT it has not increased the size or structure of our networks • The real limitations [now] are: o Lack of face-to-face interaction o Absence of endorphin-based bonding mechanisms
  26. 26. Thanks ….!

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