The coercive logic of fake news

The spread of misinformation and "fake news" continues to be a major focus of public concern. A great deal of research has examined who falls for misinformation and why, and what can be done to make people more discerning consumers of news. Comparatively little work, however, has considered misinformation producers, and how their strategies interact with the psychology of news consumers. Here we use game-theoretic models to study the strategic interaction between news publishers and news readers. We show that publishers who seek to spread misinformation can generate high engagement with falsehoods by using strategies that mix true and false stories over time, in such a way that they serve more false stories to more loyal readers. These coercive strategies cause false stories to receive higher reader engagement than true stories - even when readers strictly prefer truth over falsehood. In contrast, publishers who seek to promote engagement with accurate information will use strategies that generate more engagement with true stories than with false stories. We confirm these predictions empirically by examining 1,000 headlines from 20 mainstream and 20 fake news sites, comparing Facebook engagement data with 20,000 perceived accuracy ratings collected in a survey experiment. We show that engagement is negatively correlated with perceived accuracy among misinformation sites, but positively correlated with perceived accuracy among mainstream sites. We then use our model to analyze the conditions under which news sites seeking engagement will produce false stories. We show that if a publisher incorrectly assumes that readers prefer falsehoods, their resulting publication strategy can itself manufacture greater engagement with false news - leading to a self-reinforcing cycle of false news promotion

The distorting effects of producer strategies : why engagement does not reveal consumer preferences for misinformation

A great deal of empirical research has examined who falls for misinformation and why. Here, we introduce a formal game-theoretic model of engagement with news stories that captures the strategic interplay between (mis)information consumers and producers. A key insight from the model is that observed patterns of engagement do not necessarily reflect the preferences of consumers. This is because producers seeking to promote misinformation can use strategies that lead moderately inattentive readers to engage more with false stories than true ones—even when readers prefer more accurate over less accurate information. We then empirically test people’s preferences for accuracy in the news. In three studies, we find that people strongly prefer to click and share news they perceive as more accurate—both in a general population sample, and in a sample of users recruited through Twitter who had actually shared links to misinformation sites online. Despite this preference for accurate news—and consistent with the predictions of our model—we find markedly different engagement patterns for articles from misinformation versus mainstream news sites. Using 1,000 headlines from 20 misinformation and 20 mainstream news sites, we compare Facebook engagement data with 20,000 accuracy ratings collected in a survey experiment. Engagement with a headline is negatively correlated with perceived accuracy for misinformation sites, but positively correlated with perceived accuracy for mainstream sites. Taken together, these theoretical and empirical results suggest that consumer preferences cannot be straightforwardly inferred from empirical patterns of engagement.Peer reviewe

Conducting interactive experiments online

Online labor markets provide new opportunities for behavioral research, but conducting economic experiments online raises important methodological challenges. This particularly holds for interactive designs. In this paper, we provide a methodological discussion of the similarities and differences between interactive experiments conducted in the laboratory and online. To this end, we conduct a repeated public goods experiment with and without punishment using samples from the laboratory and the online platform Amazon Mechanical Turk. We chose to replicate this experiment because it is long and logistically complex. It therefore provides a good case study for discussing the methodological and practical challenges of online interactive experimentation. We find that basic behavioral patterns of cooperation and punishment in the laboratory are replicable online. The most important challenge of online interactive experiments is participant dropout. We discuss measures for reducing dropout and show that, for our case study, dropouts are exogenous to the experiment. We conclude that data quality for interactive experiments via the Internet is adequate and reliable, making online interactive experimentation a potentially valuable complement to laboratory studies

Religion, parochialism and intuitive cooperation

Religions promote cooperation, but they can also be divisive. Is religious cooperation intuitively parochial against atheists? Evidence supporting the social heuristics hypothesis (SHH) suggests that cooperation is intuitive, independent of religious group identity. We tested this prediction in a one-shot prisoner’s dilemma game, where 1,280 practising Christian believers were paired with either a coreligionist or an atheist and where time limits were used to increase reliance on either intuitive or deliberated decisions. We explored another dual-process account of cooperation, the self-control account (SCA), which suggests that visceral reactions tend to be selfish and that cooperation requires deliberation. We found evidence for religious parochialism but no support for SHH’s prediction of intuitive cooperation. Consistent with SCA but requiring confirmation in future studies, exploratory analyses showed that religious parochialism involves decision conflict and concern for strong reciprocity and that deliberation promotes cooperation independent of religious group identity

Turking in the time of COVID

Abstract On March 16, 2020, the US Government introduced strict social distancing protocols for the United States in an effort to stem the spread of the COVID-19 pandemic. This had an immediate major effect on the job market, with millions of Americans forced to find alternative ways to make a living from home. As online labor markets like Amazon Mechanical Turk (MTurk) play a major role in social science research, concerns have been raised that the pandemic may be reducing the diversity of subjects participating in experiments. Here, we investigate this possibility empirically. Specifically, we look at 15,539 responses gathered in 23 studies run on MTurk between February and July 2020, examining the distribution of gender, age, ethnicity, political preference, and analytic cognitive style. We find notable changes on some of the measures following the imposition of nationwide social distancing: participants are more likely to be less reflective (as measured by the Cognitive Reflection Test), and somewhat less likely to be white, Democrats (traditionally over-represented on MTurk), and experienced with MTurk. Most of these differences are explained by an influx of new participants into the MTurk subject pool who are more diverse and representative – but also less attentive – than previous MTurkers