Post on 10-Feb-2016
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Why Globalized Communication
may increase Cultural PolarizationPaper presented at
2005 International Workshop Games, Networks, and Cascades
Cornell Club (NYC), October 7-9, 2005
Andreas Flache, University of Groningen, ICS
Collaborators on general project:Michael W. Macy, Cornell UniversityJames A. Kitts, University of Washington
Flache. Globalized communication and cultural polarization 2
Cultural diversity and global communication
Two positions Increasingly global communication
homogenizes cultures E.g. Hamelink 1983
Increasingly global communication makes cultural differences and cross-cultural conflict more pronounced E.g. Huntington 1996
Flache. Globalized communication and cultural polarization 3
Concepts What is culture?
Anderson: “culture provides a set of ideas, values and beliefs that function to provide a basis for interaction and understanding among a collection of people”
Axelrod: culture is “set of individual attributes that are subject to social influence”
Globalizing communication “broader range of interaction beyond an
individuals immediate locale and across cultural groups” (Greig, 2002)
Qualitative jump through the internet
Flache. Globalized communication and cultural polarization 4
Computational models of culture formation
Models proposed by Carley, Axelrod, Mark, Latane… Homophily: the greater the similarity, the more
likely the interaction (relational dynamic). Influence: the greater the interaction, the more
similar become the interactants (opinion dynamic). Axelrod: influence is restricted to local neighbors Dynamics
Minimal initial similarity increases probability of interaction which then increases similarity leading to uniformity, not diversity
Why can there be stable diversity?
Flache. Globalized communication and cultural polarization 5
Axelrod’s solution: interaction thresholds
Influence stops when individuals are too different
preservation of diverse, isolated “subcultures”
Local regions become homogenous over time
Differentiation from neighboring regions
No more mutual influence
Stable diversity
Example of equilibrium:
5 “features”,
15 traits per feature
20x20 “world”,
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Modeling globalization: Inreasing geographical range of communication
Axelrod (1997) Increasing range less diversity
Diversity = #distinct “cultures” in equilibrium Initial distribution more similar across neighborhoods (random) more overlap, i.e. smaller chance of isolation of local regions
Follow-up studies E.g. Shibani (2001), Greig (2002) Global mass media and larger range of interaction allow local minorities to find
support against local conformity pressures Globalized communication may also increase diversity
Implications of Axelrod’s model for globalizing communication
Flache. Globalized communication and cultural polarization 7
What is missing…(1)
Continuous opinion space Axelrod etc assume nominal opinion space Many issues are not nominal
how much money should we spend on…? Many traditional models of opinion
formation use continuous space e.g. French, Harary, Abelson, Friedkin, Hegselmann &
Krause. These models produce unanimity, not
stable diversity, under a large range of conditions.
Flache. Globalized communication and cultural polarization 8
What is missing…(2)
There is no negative influence Axelrod etc assume that agents never change
opinions to decrease similarity Empirically we know: people often have a
tendency to distance oneself from “negative referents”, “profiling”
Adding negative influence in a continuous opinion space may profoundly change influence dynamics Macy et al (2002): from uniformity to
polarization (not just diversity)
Flache. Globalized communication and cultural polarization 9
A Hopfield Model of Dynamic Attraction: Modeling negative influence and continuous opinions
Nowak & Vallacher, 1997 Node i has + or – “opinion” on K dimensions (-1 ≤sik ≤ 1) Nodes i and j are tied by positive or negative
weights (-1≤wij≤1) Opinion of j can attract or repel opinion of i,
depending on wij
i jwij
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Influence depends on relations
Effect of sj on si depends on the connection between i and j Positive weights: opinions become more similar Negative weights: opinions become less similar Change in position of i with regard to issue s is
weighted average of distances sj-si modified by “moderation” m
Moderation: degree to which actors weigh small differences in opinion relatively less (m >1 “moderate” or “tolerant”)
N
j
mtitjijtiti ssw
Nss
1,,,1, )(
1N = size of neighborhood
j neighborhood
Flache. Globalized communication and cultural polarization 11
And relations depend on influence
Weight wij increases with agreement in the K opinions of i and j
To be precise: weight is adapted gradually to match level of (dis) agreement.
)1()1( 11, K
ssww
K
kjktikt
ijttij
K = number of opinions
j neighborhood
= learning rate
Flache. Globalized communication and cultural polarization 12
More details… Correction necessary to keep opinions within bounds
Asynchronous updating Agent is selected at random either weights or states are updated with equal probability
ij
m
titjjiti
ssw
Ns
2
1 ,,,
0 if),1(
0 if),1(
,,,,
,,,,1,
titititi
tititititi ssss
sssss
Flache. Globalized communication and cultural polarization 13
Access structure channels influence Mutual influence only for local
neighbors For example:
Agents are arranged on a circle Parameter range (r)
% of population to which agent has access Access is symmetrical
r=10% r=20% r=50%
Examples for N=20
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Experiment 1: Does continuous opinion space reduce diversity?
Comparison with Axelrod: no negative influence: weights are mapped linearly to 0..1 interval Zero influence only if maximum difference in opinions
From dichotomous towards continuous opinions Discreetize opinion space into g equidistant positions Gradually increase g and test effect on diversity in equilibrium. Diversity measured as # of different opinion vectors surviving. We also measured variance of opinions in equilibrium
Conservative scenario resembles conditions where Axelrod found high diversity Opinion space is one-dimensional, k=1 (few features) Strongly local interaction (circle, r=2%)
More settings:•N=100•linear influence function (moderation=1)•Fast learning (=1)•Initial opinion is uniformly distributed in -1..+1•initial weight proportional to initial agreement
Flache. Globalized communication and cultural polarization 15
Experiment 1: Results
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
diversity
variance
g = number of equidistant opinions
g > 1000 continuous opinion space
Consistent with Axelrod:
•more possible opinions increase diversity (#opinions in equilibrium)
But inconsistent with Axelrod:
•variance of opinions in equilibrium approaches zero as g increases
•No diversity at all in continuous opinion space
Flache. Globalized communication and cultural polarization 16
Experiment 2.Stable diversity in a continuous opinion space: negative influence
Experiment 1 as baseline But now continuous opinion space
k=1, N=100,… Strongly localized interaction (r=2%)
Manipulations: Positive influence only (Axelrod) vs. Positive + negative influence
weights 0..1 vs. weights -1..+1. Results
With positive influence only, unanimity in equilibrium With pos+neg, stable polarization: two maximally different
subgroups By and large, this result is robust across a large range of conditions,
e.g. for larger N, K and higher levels of m
Flache. Globalized communication and cultural polarization 17
Experiment 3: What is the effect of globalizing communication?
Experiment 2 as baseline But now always positive + negative influence of interaction
Continuous opinion space, k=1, N=100,m=1,… Manipulation
Range of interaction increases gradually from 2%..50% 10 replications per condition Outcome measures (after maximally 1000 iterations):
Diversity = #distinct opinions / N Polarization = variance of pairwise agreement Variance of states
But first an illustrative scenario: k=2, r=2%Larger range increases influence range of “extremists” no more gradual shift of opinions between neighbouring regionsagents either move towards or distance themselves from
extremistspressure towards polarization
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A stylized explanation
smokingnoye
scritical distance
disliking disagreementliking agreement
Flache. Globalized communication and cultural polarization 19
A stylized example: large interaction range
smokingnoye
scritical distance
disliking disagreementliking agreement
Tendency towards polarization
Macy, Kitts, Flache, Benard (2002)
Flache. Globalized communication and cultural polarization 20
A stylized example: small interaction range
smokingnoye
scritical distance
disliking disagreementliking agreement
Local convergence eliminates extremes cohesion when subgroups merge
Flache. Globalized communication and cultural polarization 21
0
0.2
0.4
0.6
0.8
1
1.2
Diversity
Polarization
varianceS
Experiment 3: Results
Range = size of local neighborhood in %population
Consistent with Axelrod:
•a larger range of interaction decreases diversity (#opinions in equilibrium)
But inconsistent with Axelrod:
•Stable diversity with continuous opinions
• Increasing variance of opinions with increasing range of interaction
• Increasing polarization with increasing range of interaction
Flache. Globalized communication and cultural polarization 22
k=2 moderation=2
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Diversity
Polarization
Variance
k = 2 moderation=1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Diversity
Polarization
varianceS
Positive effect of range on polarization changes,
•When number of issues (k) increasesNegative ties less likely from random
startEffect tends to become negative
•When moderation (m) increasesLarge opinion differences weigh relatively
morePositive effect becomes stronger
• Inverted U-shape effect of range possible
Range has two opposing effects:•Larger range increases overlap between
neighboring regions pressure towards conformity• ..it also increases influence range of
“extremists” pressure towards polarization
Experiment 3: Robustness tests
Flache. Globalized communication and cultural polarization 23
How can range increase polarization?The diffusion of regional conflicts
Illustrative scenario: isolated caves N=100, range=5%, k=3, moderation=1 From a random start, homogeneity develops
in most local regions, but in a small proportion of local regions polarization emerges
When ties between polarized and homogenous regions are added, agents in homogenous regions either move towards or distance themselves from extremists
Extremism spreads through random ties
Flache. Globalized communication and cultural polarization 24
Robustness tests of effects of range
Noise Qualitative effects robust against small error
in perception of others’ influence (+/- .5%) Population size
Same qualitative effects found for N=100, 200,500 Dimensions of opinion space
Polarization occurs also with higher k, but only with much higher moderation
Moderation The less moderation, the less polarization
Random access structure Qualitative effects remain unchanged
Flache. Globalized communication and cultural polarization 25
Conclusions Some previous models suggest cultural diversity
can persist despite global interaction range, other’s don’t
All rely on nominal opinion space. Model with continuous opinion space and
negative social influences generates tendency towards polarization when interaction gets global
Depending on moderation and #issues, effect of increasing range of interaction is
increasing polarization decreasing polarization Inverted U-shape
Model suggests that globalized communication may promote “diffusion of regional conflicts”
Flache. Globalized communication and cultural polarization 26
Future research Theoretical: towards analytical models
E.g. stochastic stability (Young) Empirical:
social influence in experiments / online interaction
Is there influence? Is it negative? E.g. world value survey and data on
accessibility of internet in different countries or social strata
Is there a relationship between cultural convergence / divergence and access to the internet?