Social contagion is a well-studied phenomenon in which people adopt beliefs that they are exposed to by their neighbors, and then pass those beliefs along to others. Research (and daily life) shows that people prefer to adopt beliefs that are consistent with those they already hold. However, scholars do not often account for interactions between beliefs in their models of social contagion . Instead, they assume that beliefs spread independently of one another . Is this a harmless simplification? Or does omitting interdependence between beliefs suppress important dynamics, and change the outcome of social contagion? This paper performs a head-to-head comparison between independent and interdependent diffusion. Simulations identify two social processes that emerge when diffusants interact, and predict that as a result of interdependent diffusion, worldviews will emerge that are unconstrained by external truth, and polarization will develop in homogenous populations. A controlled laboratory experimentconfirms these predictions with 2400 participants in 120 artificial social networks. I conclude that the assumption of independence between diffusants is not as universally appropriate as its ubiquity would suggest. Instead, interdependence between diffusants is likely to be both common and consequential .
Social contagion is the process in which people adopt a belief, idea, or practice from a neighbor and pass it along to someone else. For over 100 years, scholars of social contagion have almost exclusively made the same implicit assumption: that only one belief, idea, or practice spreads through the population at a time. It is a default assumption that we don't bother to state, let alone justify. The assumption is so ingrained that our literature doesn't even have a word for "whatever is to be diffused", because we have never needed to discuss more than one of them. But this assumption is obviously false. Millions of beliefs, ideas, and practices (let's call them "diffusants") spread through social media every day. To assume that diffusants spread one at a time (or more generously, that they spread independently of one another ) is to assume that interactions between diffusants have no influence on adoption patterns. This could be true, or it could be wildly off the mark. We've never stopped to find out. This paper makes a direct comparison between the spread of independent and interdependent beliefs using simulations, observational data analysis, and a 2400-subject laboratory experiment. I find that in assuming independence between diffusants , scholars have overlooked social processes that fundamentally change the outcomes of social contagion. Interdependence between beliefs generates polarization, irrespective of social network structure, homophily, demographics, politics, or any other commonly cited cause. It also leads to the emergence of popular worldviews that are unconstrained by ground truth .
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beliefs that they are exposed to by their neighbors, and then pass those beliefs along to others. Research (and daily life) shows that people prefer to adopt beliefs that are consistent with those they already hold. However, scholars do not often account for interactions between beliefs in their models
a belief, idea, or practice from a neighbor and pass it along to someone else. For over 100 years, scholars
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. Instead, they assume that beliefs spread
have almost exclusively made the same implicit assumption: that only one belief, idea, or practice spreads through the population at a time. It is a default assumption that we don't bother to state, let alone justify. The assumption is so ingrained that our literature doesn't even have a word for "whatever is to be diffused", because we have never needed to discuss more than one of them. But this assumption is obviously false. Millions of beliefs, ideas, and practices (let's call them "diffusants") spread through social media every day. To assume that diffusants spread one at a time (or more generously, that they spread
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. Is this a harmless simplification? Or does omitting interdependence between beliefs suppress important dynamics, and change the outcome of social contagion? This paper performs a head-to-head comparison between
) is to assume that interactions between diffusants have no influence on adoption patterns. This could be true, or it could be wildly off the mark. We've never stopped to find out. This paper makes a direct comparison between the spread of
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diffusion. Simulations identify two social processes that emerge when diffusants interact, and predict that as a result of interdependent diffusion, worldviews will emerge that are unconstrained by external truth, and polarization will develop in homogenous populations. A controlled laboratory experimentconfirms these predictions with 2400 participants in 120 artificial social networks. I conclude that the assumption of
beliefs using simulations, observational data analysis, and a 2400-subject laboratory experiment. I find that in assuming
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is not as universally appropriate as its ubiquity would suggest. Instead, interdependence between diffusants is likely to be both common and consequential
, scholars have overlooked social processes that fundamentally change the outcomes of social contagion. Interdependence between beliefs generates polarization, irrespective of social network structure, homophily, demographics, politics, or any other commonly cited cause. It also leads to the emergence of popular worldviews that are unconstrained by ground truth