Abstract
There is public and scholarly debate about the effects of personalized recommender systems implemented in online social networks, online markets, and search engines. Some have warned that personalization algorithms reduce the diversity of information diets which confirms users’ previously held attitudes and beliefs. This, in turn, fosters the emergence opinion polarization. Critics of this personalization-polarization hypothesis argue that the effects of personalization on information diets are too weak to have meaningful effects. Here, we show that contributions to both sides of the debate fail to consider the complexity that arises when large numbers of interdependent individuals interact and exert influence on one another in algorithmically governed communication systems. Summarizing insights derived from formal models of social networks, we demonstrate that opinion dynamics can be critically influenced by mechanisms active on three levels of analysis: the individual, local, and global level. We show that theoretical and empirical research on these three levels is needed before one can determine whether personalization actually fosters polarization or not. We describe how the complexity approach can be used to anticipate and prevent undesired effects of communication technology on public debate and democratic decision-making.
Highlights
Political events such as the Brexit referendum, the election of Donald Trump, and the success of populist politicians in European and Latin-American democracies have sparked an intensive public and scholarly discussion about the effects of online communication technology on public debate and collective decision-making
Summarizing insights derived from formal models of social networks, we demonstrate that opinion dynamics can be critically influenced by mechanisms active on three levels of analysis: the individual, local, and global level
There is public and scholarly debate about the hypothesis that the personalization technology of online services contributes to the polarization of political opinions
Summary
Political events such as the Brexit referendum, the election of Donald Trump, and the success of populist politicians in European and Latin-American democracies have sparked an intensive public and scholarly discussion about the effects of online communication technology on public debate and collective decision-making. The complexity arising from communication in networks has been on social scientists’ research agenda since the 1950s and has attracted attention from fields as diverse as physics, computer science, mathematics, economics, philosophy, sociology, and political science [47,49,93] In this literature, formal models of social influence in networks were developed where network nodes exert social influence on the opinions of their network contacts. We demonstrate that models’ predictions about the effects of personalization on polarization hinge on assumptions about (i) individual behavior, (ii) individuals’ local information environment and local communication structure, and (iii) global characteristics of the whole communication network We conclude that these aspects need to be studied both theoretically and empirically before one should draw conclusions about the effects of personalization and we criticize that prominent contributions to the debate have so far failed to do so. We sketch an agenda for future research and the design of personalization technology that prevents opinion polarization
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