ABSTRACT The rise of social media has correlated with an increase in political polarization, which many perceive as a threat to public discourse and democratic governance. This paper presents a framework, drawing on social epistemology and the economic theory of public goods, to explain how social media can contribute to polarization, making us collectively poorer, even while it provides a preferable media experience for individual consumers. Collective knowledge and consensus is best served by having richly connected networks that are epistemically (...) integrated: individuals with diverse levels of expertise should be relatively well connected to each other. In epistemically segregated networks, by contrast, we have reason to predict collective epistemic failures. Expert knowledge will be isolated from the majority, leading average opinion to be less informed than is socially optimal, and entrenching disagreements. Because social media enables users to very easily adopt homophilous network connections – connections to those with similar opinions, education levels, and social backgrounds – it is likely to have increased epistemic segregation compared to older media platforms. The paper explains the theoretical foundations of these predictions, and sketches regulatory measures – such as taxes – that might be employed to preserve the public good of a well integrated social media network. (shrink)

John Stuart Mill advocated for increased interactions between individuals of dissenting opinions for the reason that it would improve society. Whether Mill and similar arguments that advocate for opinion diversity are valid depends on background assumptions about the psychology and sociality of individuals. The field of opinion dynamics is a burgeoning testing ground for how different combinations of sociological and psychological facts contribute to phenomena that affect opinion diversity, such as polarization. This paper applies some recent results from the opinion (...) dynamics literature to assess the impacts of the Millian suggestion. The goal is to understand how the scope of the validity of Mill-style arguments depends on plausible assumptions that can be formalized using agent-based models, a common modeling approach in opinion dynamics. The most salient insight is that homophily (increased interactions between like-minded individuals) does not sufficiently explain decreased opinion diversity. Hence, decreasing homophily by increasing interactions between individuals of dissenting opinions is not the simple solution that a Millian-style argument may advocate. (shrink)

Proponents of epistemic partiality in friendship argue that friendship makes demands of our epistemic lives that are at least inconsistent with the demands of epistemic propriety, and perhaps downright irrational. In this paper, I focus on the possibility that our commitments to our friends distort how we respond to testimony about them, their character, and their conduct. Sometimes friendship might require us to ignore (or substantially underweight) what others tell us about our friends. However, while this practice might help promote (...) your friendship and protect your friends, refusing someone’s testimony can constitute a special kind of insult towards them, according to Allen Hazlett (2017) and Finlay Malcolm (2018). It seems to follow that friendship can require us to insult people by refusing their testimony. This should count against treating your friends with epistemic partiality, one might think. It’s plausible that we have moral reasons not to insult other people, whether they’re our friends or not. The risk of insulting non-friends, it turns out, is just the beginning of the problems for the epistemic partiality in friendship. Recent discussions in social epistemology, led by Miranda Fricker (2007), Kristie Dotson (2011) and José Medina (2012), among others, have brought renewed attention the distinctly epistemic nature of some kinds of injustice. Drawing on this work, I’ll suggest a principled way to determine when epistemic partiality in friendship is morally impermissible because of the genuine risk of harmful epistemic injustice. -/- The paper proceeds as follows. First, I’ll argue that treating our friends with epistemic partiality can involve insulting other people by refusing their testimony. Then I’ll consider whether we ever ought to commit more morally serious testimonial injustices in the name of friendship. After considering some putative cases, I’ll introduce the concept of testimonial injustice, referring primarily to the work of Dotson (2011). I’ll explain how and why the epistemic bias which I’ve prescribed in friendship could be thought to cause such injustice. Drawing on the work of Sheila Lintott (2015), I’ll consider some ways in which the extent of the testimonial injustice caused by bias in friendship might be worse yet, namely, because of the role that homophily plays in determining who we become (and remain) friends with. In particular, I’ll consider whether epistemic partiality perpetuates racist or sexist forms of testimonial injustice. Finally, I’ll attempt to alleviate some of these concerns and determine when we’re morally required to treat friends with epistemic partiality. I’ll argue that whilst protecting a friend’s well-being might require you to cause testimonial injustice, such injustice would be morally unjustified. Accordingly, if you commit such injustice in the name of friendship, you’re morally blameworthy for doing so. This, I suggest, imposes an additional limit on epistemic partiality in friendship. (shrink)

Spatially situated opinions that can be held with different degrees of conviction lead to spatiotemporal patterns such as clustering (homophily), polarization, and deadlock. Our goal is to understand how sensitive these patterns are to changes in the local nature of interactions. We introduce two different mixing mechanisms, spatial relocation and nonlocal interaction (“telephoning”), to an earlier fully spatial model (no mixing). Interestingly, the mechanisms that create deadlock in the fully spatial model have the opposite effect when there is a (...) sufficient amount of mixing. With telephoning, not only is polarization and deadlock broken up, but consensus is hastened. The effects of mixing by relocation are even more pronounced. Further insight into these dynamics is obtained for selected parameter regimes via comparison to the mean-field differential equations. (shrink)

Beyond belief change and meme adoption, both genetics and infection have been spoken of in terms of information transfer. What we examine here, concentrating on the specific case of transfer between sub-networks, are the differences in network dynamics in these cases: the different network dynamics of germs, genes, and memes. Germs and memes, it turns out, exhibit a very different dynamics across networks. For infection, measured in terms of time to total infection, it is network type rather than degree of (...) linkage between sub-networks that is of primary importance. For belief transfer, measured in terms of time to consensus, it is degree of linkage rather than network type that is crucial. Genes model each of these other dynamics in part, but match neither in full. For genetics, like belief transfer and unlike infection, network type makes little difference. Like infection and unlike belief, on the other hand, the dynamics of genetic information transfer within single and between linked networks are much the same. In ways both surprising and intriguing, transfer of genetic information seems to be robust across network differences crucial for the other two. (shrink)

In order to understand the transmission of a disease across a population we will have to understand not only the dynamics of contact infection but the transfer of health-care beliefs and resulting health-care behaviors across that population. This paper is a first step in that direction, focusing on the contrasting role of linkage or isolation between sub-networks in (a) contact infection and (b) belief transfer. Using both analytical tools and agent-based simulations we show that it is the structure of a (...) network that is primary for predicting contact infection—whether the networks or sub-networks at issue are distributed ring networks or total networks (hubs, wheels, small world, random, or scale-free for example). Measured in terms of time to total infection, degree of linkage between sub-networks plays a minor role. The case of belief is importantly different. Using a simplified model of belief reinforcement, and measuring belief transfer in terms of time to community consensus, we show that degree of linkage between sub-networks plays a major role in social communication of beliefs. Here, in contrast to the case of contract infection, network type turns out to be of relatively minor importance. What you believe travels differently. In a final section we show that the pattern of belief transfer exhibits a classic power law regardless of the type of network involved. (shrink)