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HHaass tthhee IInntteerrnneett CChhaannggeedd 
OOuurr SSoocciiaall WWoorrlldd?? 
Robin Dunbar
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?
Social Brain Hypothesis 
• Predicted group size 
for humans is ~150 
• “Dunbar’s Number” 
Monkeys 
Apes 
Neocortex volume divided by rest of brain
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
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)
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
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
BUT….our friends are NOT all the same! 
Our social world is less like this 
…..and more like this
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
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)
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
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
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)
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
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
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]
• 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?
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
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)
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)
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)
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
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
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
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
Thanks ….!

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

  • 1. HHaass tthhee IInntteerrnneett CChhaannggeedd OOuurr SSoocciiaall WWoorrlldd?? Robin Dunbar
  • 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. Social Brain Hypothesis • Predicted group size for humans is ~150 • “Dunbar’s Number” Monkeys Apes Neocortex volume divided by rest of brain
  • 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. 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. 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. 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. BUT….our friends are NOT all the same! Our social world is less like this …..and more like this
  • 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. 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. 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. 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. 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. 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. 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. 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. • 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. 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. 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. 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. 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. 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. 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. 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. 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