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Emergence of collective memories

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Presentation of this paper:
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0012522

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Emergence of collective memories

  1. 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. 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. 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. 4. Empirical memory web Source material Bearman, Moody, Faris, 2003. “Networks and History” Complexity 8:61–71.
  5. 5. Empirical memory web Individual memory web 1 Bearman, Moody, Faris, 2003. “Networks and History” Complexity 8:61–71.
  6. 6. Empirical memory web Individual memory web 2 Bearman, Moody, Faris, 2003. “Networks and History” Complexity 8:61–71.
  7. 7. Empirical memory web Aggregate memory web Bearman, Moody, Faris, 2003. “Networks and History” Complexity 8:61–71.
  8. 8. Empirical memory web Degree distribution
  9. 9. Empirical memory web Clustering coefficient vs. degree
  10. 10. Empirical memory web Degree correlations
  11. 11. Empirical memory web Community structure
  12. 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. 13. Communication model Learning dynamics
  14. 14. Example output Memory overlap
  15. 15. 15   Community structure dynamics Number of groups
  16. 16. Model community structure Number of groups
  17. 17. Model community structure Memories and social ties
  18. 18. 18   Model community structure Size- & communication-rate scaling of the number of communities
  19. 19. Model community structure Size-scaling of the diversity regime
  20. 20. Model community structure Size-scaling of the diversity regime
  21. 21. Model community structure Size-scaling of the number of groups
  22. 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. 23. Petter 谢谢⼤大家! Sungmin Verónica http://www.tp.umu.se/~holme/
  24. 24. Model community structure Why a peak i?
  25. 25. Communication model Errors & misinterpretations

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