Why Globalized Communication may increase Cultural Polarization

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


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


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?


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”,


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


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.


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)


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


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


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


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


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


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


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


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


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


A stylized explanation

smokingnoye

scritical distance

disliking disagreementliking agreement


A stylized example: large interaction range

smokingnoye

scritical distance


Tendency towards polarization

Macy, Kitts, Flache, Benard (2002)


A stylized example: small interaction range

smokingnoye

scritical distance


Local convergence eliminates extremes cohesion when subgroups merge


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


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


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


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


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”


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?

Why Globalized Communication may increase Cultural Polarization

Documents

Transcript of Why Globalized Communication may increase Cultural Polarization