1.
THE EMERGENCE OF COLLECTIVE MEMORIES
Sungmin Lee 李圣民 (Umeå University 于默奥⼤大学, 瑞典)
Verónica Ramenzoni (MPI Psycholinguistics Nijmegen, Holland)
Petter Holme 郝培德 (Umeå University 于默奥⼤大学, 瑞典,
Sungkyunguan University 成韵馆⼤大学，韩国)
PLoS ONE 5, e12522 (2010).
http://www.tp.umu.se/~holme/
全国复杂⺴⽹网络学术会议
October 17, 2010

2.
培德在苏州
complex network
boom of early 00’s
Narrative network 叙述⺴⽹网络
≈ Memory web 记忆⺴⽹网络
research leader
fieldtrip to 北京

3.
Outline
- What is the topology of real narrative networks?
- How can we model the evolution of narrative
networks / memory webs?
- How (much) can communication stabilize
collective memories?
- What are the conditions for groups to form?
- How does the observations behave as a function
of population size?

4.
Empirical memory web
Source material
Bearman, Moody, Faris, 2003. “Networks and History” Complexity 8:61–71.

5.
Empirical memory web
Individual memory web 1
Bearman, Moody, Faris, 2003. “Networks and History” Complexity 8:61–71.

6.
Empirical memory web
Individual memory web 2
Bearman, Moody, Faris, 2003. “Networks and History” Complexity 8:61–71.

7.
Empirical memory web
Aggregate memory web
Bearman, Moody, Faris, 2003. “Networks and History” Complexity 8:61–71.

8.
Empirical memory web
Degree distribution

9.
Empirical memory web
Clustering coefficient vs. degree

10.
Empirical memory web
Degree correlations

11.
Empirical memory web
Community structure

12.
Model ingredients
- N agents with individual memory webs.
- Agents can learn about history from experience or
communication.
- Closer friends are more likely to communicate &
people who communicate often are closer friends.
- Events / associative arcs remembered more strongly
are more frequently discussed, and vice versa.
- Events / associative arcs not talked about are
gradually forgotten.

13.
Communication model
Learning dynamics

14.
Example output
Memory overlap

15.
15
Community structure dynamics
Number of groups

16.
Model community structure
Number of groups

17.
Model community structure
Memories and social ties

18.
18
Model community structure
Size- & communication-rate scaling of the number of
communities

19.
Model community structure
Size-scaling of the diversity regime

20.
Model community structure
Size-scaling of the diversity regime

21.
Model community structure
Size-scaling of the number of groups

22.
Summary
- Narrative networks represent memory webs.
- Network modeling can be helpful to understand
these quantitatively.
- An empirical narrative network shows skewed (in-
and out-) degree distribution.
- Propose a communication model that shows the
emergence of collective memories
- … and the formation of communities with strong
internal connections and similar memory webs.
- The number of communities is limited as a function
of N

23.
Petter
谢谢⼤大家！
Sungmin
Verónica
http://www.tp.umu.se/~holme/

24.
Model community structure
Why a peak i?

25.
Communication model
Errors & misinterpretations