Misinformation does not reduce trust in accurate search results, but warning banners may backfire.

People rely on search engines for information in critical contexts, such as public health emergencies-but what makes people trust some search results more than others? Can search engines influence people's levels of trust by controlling how information is presented? And, how does the presence of misinformation influence people's trust? Research has identified both rank and the presence of misinformation as factors impacting people's search behavior. Here, we extend these findings by measuring the effects of these factors, as well as misinformation warning banners, on the perceived trustworthiness of individual search results. We conducted three online experiments (N = 3196) using Covid-19-related queries, and found that although higher-ranked results are clicked more often, they are not more trusted. We also showed that misinformation does not damage trust in accurate results displayed below it. In contrast, while a warning about unreliable sources might decrease trust in misinformation, it significantly decreases trust in accurate information. This research alleviates some concerns about how people evaluate the credibility of information they find online, while revealing a potential backfire effect of one misinformation-prevention approach; namely, that banner warnings about source unreliability could lead to unexpected and nonoptimal outcomes in which people trust accurate information less.

A theory of emergence: Knowledge, rewiring and innovation.

Why do social interactions linked to sharing knowledge drive the emergence of a regional technology economy? We proffer a positive theory and explanation-sketch identifying mechanisms and initial conditions in an explanation of emergence of a knowledge economy. We trace the emergence of a knowledge economy, from a small group of founding members to a regional technology economy. With the rapid influx of new people, knowledge spillover motivates technologists and entrepreneurs to reach out beyond existing contacts to explore the expanding knowledge economy and interact with new acquaintances in the search for novelty. In the course of network rewiring in knowledge clusters, individuals share knowledge and cooperate in innovation, and move to more central positions when they interact. Mirroring the trends of increased knowledge exploration and innovative activity at the individual level, new startup firms founded during this time period come to span a greater number of industry groups. Endogenous dynamics of overlapping knowledge networks lie behind the rapid morphogenesis of new regional technology economies in New York City and Los Angeles.

Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections.

Social media has been transforming political communication dynamics for over a decade. Here using nearly a billion tweets, we analyse the change in Twitter's news media landscape between the 2016 and 2020 US presidential elections. Using political bias and fact-checking tools, we measure the volume of politically biased content and the number of users propagating such information. We then identify influencers-users with the greatest ability to spread news in the Twitter network. We observe that the fraction of fake and extremely biased content declined between 2016 and 2020. However, results show increasing echo chamber behaviours and latent ideological polarization across the two elections at the user and influencer levels.

Polarization and tipping points.

Research has documented increasing partisan division and extremist positions that are more pronounced among political elites than among voters. Attention has now begun to focus on how polarization might be attenuated. We use a general model of opinion change to see if the self-reinforcing dynamics of influence and homophily may be characterized by tipping points that make reversibility problematic. The model applies to a legislative body or other small, densely connected organization, but does not assume country-specific institutional arrangements that would obscure the identification of fundamental regularities in the phase transitions. Agents in the model have initially random locations in a multidimensional issue space consisting of membership in one of two equal-sized parties and positions on 10 issues. Agents then update their issue positions by moving closer to nearby neighbors and farther from those with whom they disagree, depending on the agents' tolerance of disagreement and strength of party identification compared to their ideological commitment to the issues. We conducted computational experiments in which we manipulated agents' tolerance for disagreement and strength of party identification. Importantly, we also introduced exogenous shocks corresponding to events that create a shared interest against a common threat (e.g., a global pandemic). Phase diagrams of political polarization reveal difficult-to-predict transitions that can be irreversible due to asymmetric hysteresis trajectories. We conclude that future empirical research needs to pay much closer attention to the identification of tipping points and the effectiveness of possible countermeasures.

It's not just how the game is played, it's whether you win or lose.

Growing disparities of income and wealth have prompted extensive survey research to measure the effects on public beliefs about the causes and fairness of economic inequality. However, observational data confound responses to unequal outcomes with highly correlated inequality of opportunity. This study uses a novel experiment to disentangle the effects of unequal outcomes and unequal opportunities on cognitive, normative, and affective responses. Participants were randomly assigned to positions with unequal opportunities for success. Results showed that both winners and losers were less likely to view the outcomes as fair or attributable to skill as the level of redistribution increased, but this effect of redistribution was stronger for winners. Moreover, winners were generally more likely to believe that the game was fair, even when the playing field was most heavily tilted in their favor. In short, it's not just how the game is played, it's also whether you win or lose.

The strength of long-range ties in population-scale social networks.

Long-range connections that span large social networks are widely assumed to be weak, composed of sporadic and emotionally distant relationships. However, researchers historically have lacked the population-scale network data needed to verify the predicted weakness. Using data from 11 culturally diverse population-scale networks on four continents-encompassing 56 million Twitter users and 58 million mobile phone subscribers-we find that long-range ties are nearly as strong as social ties embedded within a small circle of friends. These high-bandwidth connections have important implications for diffusion and social integration.

The social contagion of generosity.

Why do people help strangers when there is a low probability that help will be directly reciprocated or socially rewarded? A possible explanation is that these acts are contagious: those who receive or observe help from a stranger become more likely to help others. We test two mechanisms for the social contagion of generosity among strangers: generalized reciprocity (a recipient of generosity is more likely to pay it forward) and third-party influence (an observer of generous behavior is more likely to emulate it). We use an online experiment with randomized trials to test the two hypothesized mechanisms and their interaction by manipulating the extent to which participants receive and observe help. Results show that receiving help can increase the willingness to be generous towards others, but observing help can have the opposite effect, especially among those who have not received help. These results suggest that observing widespread generosity may attenuate the belief that one's own efforts are needed.

Diurnal and seasonal mood vary with work, sleep, and daylength across diverse cultures.

We identified individual-level diurnal and seasonal mood rhythms in cultures across the globe, using data from millions of public Twitter messages. We found that individuals awaken in a good mood that deteriorates as the day progresses--which is consistent with the effects of sleep and circadian rhythm--and that seasonal change in baseline positive affect varies with change in daylength. People are happier on weekends, but the morning peak in positive affect is delayed by 2 hours, which suggests that people awaken later on weekends.

The false enforcement of unpopular norms.

Prevailing theory assumes that people enforce norms in order to pressure others to act in ways that they approve. Yet there are numerous examples of "unpopular norms" in which people compel each other to do things that they privately disapprove. While peer sanctioning suggests a ready explanation for why people conform to unpopular norms, it is harder to understand why they would enforce a norm they privately oppose. The authors argue that people enforce unpopular norms to show that they have complied out of genuine conviction and not because of social pressure. They use laboratory experiments to demonstrate this "false enforcement" in the context of a wine tasting and an academic text evaluation. Both studies find that participants who conformed to a norm due to social pressure then falsely enforced the norm by publicly criticizing a lone deviant. A third study shows that enforcement of a norm effectively signals the enforcer's genuine support for the norm. These results demonstrate the potential for a vicious cycle in which perceived pressures to conform to and falsely enforce an unpopular norm reinforce one another.

Trust, cooperation, and market formation in the U.S. and Japan.

Compared with the U.S., Japan is believed to have a collectivist culture that nurtures high trust. Results from laboratory and survey research, however, show that Americans are more likely to trust strangers than are Japanese. Why would trust be lower in a collectivist culture? We use an agent-based computational model to explore the evolutionary origin of this puzzling empirical finding. Computer simulations suggest that higher social mobility in the U.S. may be the explanation. With low mobility, agents rarely encounter strangers and thus remain highly parochial, trusting only their neighbors and avoiding open-market transactions with outsiders. With moderate mobility, agents learn to read telltale signs of character so that they can take advantage of better opportunities outside the neighborhood. However, if mobility is too great, there is too little trustworthiness to make the effort to discriminate worthwhile. This finding suggests that higher mobility in the U.S. may explain why Americans are more trusting than Japanese, but if mobility becomes too high, the self-reinforcing high-trust equilibrium could collapse.

Learning dynamics in social dilemmas.

The Nash equilibrium, the main solution concept in analytical game theory, cannot make precise predictions about the outcome of repeated mixed-motive games. Nor can it tell us much about the dynamics by which a population of players moves from one equilibrium to another. These limitations, along with concerns about the cognitive demands of forward-looking rationality, have motivated efforts to explore backward-looking alternatives to analytical game theory. Most of the effort has been invested in evolutionary models of population dynamics. We shift attention to a learning-theoretic alternative. Computational experiments with adaptive agents identify a fundamental solution concept for social dilemmas--stochastic collusion--based on a random walk from a self-limiting noncooperative equilibrium into a self-reinforcing cooperative equilibrium. However, we show that this solution is viable only within a narrow range of aspiration levels. Below the lower threshold, agents are pulled into a deficient equilibrium that is a stronger attractor than mutual cooperation. Above the upper threshold, agents are dissatisfied with mutual cooperation. Aspirations that adapt with experience (producing habituation to stimuli) do not gravitate into the window of viability; rather, they are the worst of both worlds. Habituation destabilizes cooperation and stabilizes defection. Results from the two-person problem suggest that applications to multiplex and embedded relationships will yield unexpected insights into the global dynamics of cooperation in social dilemmas.