Science Advances

Supplementary Materials

This PDF file includes:

  • section S1. Summarizing ICEWS
  • section S2. Measuring influence using CCM
  • section S3. Characterizing instances of reciprocity
  • section S4. Varying thresholds for CCM reciprocity
  • section S5. Country pairs with asymmetric influence
  • fig. S1. The distributions of Goldstein scores by CAMEO event type occurring in the ICEWS data set.
  • fig. S2. The distribution of CAMEO quad classes in the ICEWS data set.
  • fig. S3. The number of events per day during the entire ICEWS data set.
  • fig. S4. Gaps in interactions between country pairs are small.
  • fig. S5. An example from dynamical systems.
  • fig. S6. Examples of shadow manifolds.
  • fig. S7. Using nearest neighbors of shadow manifolds to recover variable
    dynamics.
  • fig. S8. Using CCM to infer causality between using United States (USA) treatment of Saudi Arabia (SAU) and Saudi Arabia’s treatment of the United States (E = 200, τ = 1).
  • fig. S9. The number of pairs of countries exhibiting CCM reciprocity (y axis) during four 5-year time periods (x axis) as we vary the minimum influence threshold (that is, minimum Pearson correlation of CCM reconstruction, indicated by color).
  • fig. S10. CCM causation decreases with increased artificial noise.
  • fig. S11. The effects of biased news data (λ = 0.00).
  • fig. S12. The effects of biased news data (λ = 0.10).
  • fig. S13. The effects of biased news data (λ = 0.20).
  • fig. S14. The effects of biased news data (λ = 0.30).
  • fig. S15. The effects of biased news data (λ = 0.40).
  • fig. S16. The effects of biased news data (λ = 0.50).
  • fig. S17. The effects of biased news data (λ = 0.60).
  • fig. S18. The effects of biased news data (λ = 0.70).
  • fig. S19. The effects of biased news data (λ = 0.80).
  • fig. S20. The effects of biased news data (λ = 0.90).
  • fig. S21 . Main results using CCM analysis with E = 200 and τ = 2.
  • fig. S22. Main results using CCM analysis with E = 200 and τ = 3.
  • fig. S23. Main results using CCM analysis with E = 200 and τ = 4.
  • fig. S24. Main results using CCM analysis with E = 200 and τ = 5.
  • fig. S25. Country pairs exhibiting CCM reciprocity are more likely to reciprocate cooperation or conflict.
  • fig. S26. The patterns of behavior in the day following an interaction.
  • fig. S27. The patterns of behavior in the three days following an interaction.
  • fig. S28. The patterns of behavior in the week following an interaction.
  • fig. S29. The patterns of behavior in the month following an interaction.
  • fig. S30. The effects of varying the CCM threshold for causality.
  • fig. S31. Pairs of countries exhibiting CCM reciprocity that is, CCM(A, B) ≥ 0.15 and CCM(B, A) ≥ 0.15 are connected using yellow edges.
  • fig. S32. Pairs of countries exhibiting CCM reciprocity that is, CCM(A, B) ≥ 0.15 and CCM(B, A) ≥ 0.20 are connected using yellow edges.
  • fig. S33. Pairs of countries exhibiting CCM reciprocity that is, CCM(A, B) ≥ 0.15 and CCM(B, A) ≥ 0.25 are connected using yellow edges.
  • fig. S34. Pairs of countries exhibiting CCM reciprocity that is, CCM(A, B) ≥ 0.15 and CCM(B, A) ≥ 0.30 are connected using yellow edges.
  • fig. S35. Pairs of countries exhibiting CCM reciprocity that is, CCM(A, B) ≥ 0.15 and CCM(B, A) ≥ 0.35 are connected using yellow edges.
  • fig. S36. Pairs of countries exhibiting CCM reciprocity that is, CCM(A, B) ≥ 0.15 and CCM(B, A) ≥ 0.40 are connected using yellow edges.
  • fig. S37. Pairs of countries exhibiting CCM reciprocity that is, CCM(A, B) ≥ 0.15 and CCM(B, A) ≥ 0.45 are connected using yellow edges.
  • fig. S38. Pairs of countries exhibiting CCM reciprocity that is, CCM(A, B) ≥ 0.15 and CCM(B, A) ≥ 0.50 are connected using yellow edges.
  • table S1. Nations ordered by total imposed influence.
  • table S2. The Pearson correlation for proportion of interactions of each quad class between a pair of countries to the shared influence for that pair of countries.
  • table S3. Country pairs ordered by increasing absolute difference in directed influence that is, CCM(A, B) − CCM(B, A).

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