Why Globalized Communication may increase Cultural Polarization Paper 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 University James A. Kitts, University of Washington

Flache. Globalized communication and cultural polarization2 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 polarization3 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 polarization4 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 polarization5 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”,

Flache. Globalized communication and cultural polarization6 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 polarization7 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 polarization8 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 polarization9 A Hopfield Model of Dynamic Attraction: Modeling negative influence and continuous opinions Nowak & Vallacher, 1997 Node i has + or – “opinion” on K dimensions (-1 ≤s ik ≤ 1) Nodes i and j are tied by positive or negative weights (-1≤w ij ≤1) Opinion of j can attract or repel opinion of i, depending on w ij ij w ij

Flache. Globalized communication and cultural polarization10 Influence depends on relations Effect of s j on s i 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 s j -s i modified by “moderation” m Moderation: degree to which actors weigh small differences in opinion relatively less (m >1 “moderate” or “tolerant”) N = size of neighborhood j  neighborhood

Flache. Globalized communication and cultural polarization11 And relations depend on influence Weight w ij increases with agreement in the K opinions of i and j To be precise: weight is adapted gradually to match level of (dis) agreement. K = number of opinions j  neighborhood = learning rate

Flache. Globalized communication and cultural polarization12 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

Flache. Globalized communication and cultural polarization13 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

Flache. Globalized communication and cultural polarization14 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 initial weight proportional to initial agreement

Flache. Globalized communication and cultural polarization15 Experiment 1: Results 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 polarization16 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 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 polarization17 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 regions  agents either move towards or distance themselves from extremists  pressure towards polarization

Flache. Globalized communication and cultural polarization18 A stylized explanation smoking noyes critical distance disliking  disagreement liking  agreement

Flache. Globalized communication and cultural polarization19 A stylized example: large interaction range smoking noyes critical distance disliking  disagreement liking  agreement Tendency towards polarization Macy, Kitts, Flache, Benard (2002)

Flache. Globalized communication and cultural polarization20 A stylized example: small interaction range smoking noyes critical distance disliking  disagreement liking  agreement Local convergence eliminates extremes  cohesion when subgroups merge

Flache. Globalized communication and cultural polarization21 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 polarization22 Positive effect of range on polarization changes, When number of issues (k) increases Negative ties less likely from random start Effect tends to become negative When moderation (m) increases Large opinion differences weigh relatively more Positive 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 polarization23 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 polarization24 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 polarization25 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 polarization26 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?