Prestige and content biases together shape the cultural transmission of narratives

Investigating the effects of social information on spite in an online game

While humans are highly cooperative, they can also behave spitefully. Yet spite remains understudied. Spite can be normatively driven and while previous experiments have found some evidence that cooperation and punishment may spread via social learning, no experiments have considered the social transmission of spiteful behaviour. Here we present an online experiment where, following an opportunity to earn wealth, we asked participants to choose an action towards an anonymous partner across a full spectrum of social behaviour, from spite to altruism. In accordance with cultural evolutionary theory, participants were presented with social information that varied in source and content. Across six conditions, we informed participants that either the majority or the highest earner had chosen to behave spitefully, neutrally or altruistically. We found an overall tendency towards altruism, but at lower levels among those exposed to spite compared with altruism. We found no difference between social information that came from the majority or the highest earner. Exploratory analysis revealed that participants' earnings negatively correlated with altruistic behaviour. Our results contrast with previous literature that report high rates of spite in experimental samples and a greater propensity for individuals to copy successful individuals over the majority.

Perceived experts are prevalent and influential within an antivaccine community on Twitter

Perceived experts (i.e. medical professionals and biomedical scientists) are trusted sources of medical information who are especially effective at encouraging vaccine uptake. The role of perceived experts acting as potential antivaccine influencers has not been characterized systematically. We describe the prevalence and importance of antivaccine perceived experts by constructing a coengagement network of 7,720 accounts based on a Twitter data set containing over 4.2 million posts from April 2021. The coengagement network primarily broke into two large communities that differed in their stance toward COVID-19 vaccines, and misinformation was predominantly shared by the antivaccine community. Perceived experts had a sizable presence across the coengagement network, including within the antivaccine community where they were 9.8% of individual, English-language users. Perceived experts within the antivaccine community shared low-quality (misinformation) sources at similar rates and academic sources at higher rates compared to perceived nonexperts in that community. Perceived experts occupied important network positions as central antivaccine users and bridges between the antivaccine and provaccine communities. Using propensity score matching, we found that perceived expertise brought an influence boost, as perceived experts were significantly more likely to receive likes and retweets in both the antivaccine and provaccine communities. There was no significant difference in the magnitude of the influence boost for perceived experts between the two communities. Social media platforms, scientific communications, and biomedical organizations may focus on more systemic interventions to reduce the impact of perceived experts in spreading antivaccine misinformation.

Large language models show human-like content biases in transmission chain experiments

As the use of large language models (LLMs) grows, it is important to examine whether they exhibit biases in their output. Research in cultural evolution, using transmission chain experiments, demonstrates that humans have biases to attend to, remember, and transmit some types of content over others. Here, in five preregistered experiments using material from previous studies with human participants, we use the same, transmission chain-like methodology, and find that the LLM ChatGPT-3 shows biases analogous to humans for content that is gender-stereotype-consistent, social, negative, threat-related, and biologically counterintuitive, over other content. The presence of these biases in LLM output suggests that such content is widespread in its training data and could have consequential downstream effects, by magnifying preexisting human tendencies for cognitively appealing and not necessarily informative, or valuable, content.

The role and influence of perceived experts in an anti-vaccine misinformation community

The role of perceived experts (i.e., medical professionals and biomedical scientists) as potential anti-vaccine influencers has not been characterized systematically. We describe the prevalence and importance of anti-vaccine perceived experts by constructing a coengagement network based on a Twitter data set containing over 4.2 million posts from April 2021. The coengagement network primarily broke into two large communities that differed in their stance toward COVID-19 vaccines, and misinformation was predominantly shared by the anti-vaccine community. Perceived experts had a sizable presence within the anti-vaccine community and shared academic sources at higher rates compared to others in that community. Perceived experts occupied important network positions as central anti-vaccine nodes and bridges between the anti- and pro-vaccine communities. Perceived experts received significantly more engagements than other individuals within the anti- and pro-vaccine communities and there was no significant difference in the influence boost for perceived experts between the two communities. Interventions designed to reduce the impact of perceived experts who spread anti-vaccine misinformation may be warranted.

Pseudoexpertise: A Conceptual and Theoretical Analysis

Some people publicly pretend to be experts while not being ones. They are pseudoexperts, and their presence seems to be ubiquitous in the current cultural landscape. This manuscript explores the nature and mechanisms of pseudoexpertise. We first provide a conceptual analysis of pseudoexperts based on prototypical cases of pseudoexpertise and recent philosophical work on the concept of expertise. This allows us to propose a definition that captures real-world cases of pseudoexpertise, distinguishes it from related but different concepts such as pseudoscience, and highlights what is wrong with pseudoexpertise. Next, based on this conceptual analysis, we propose a framework for further research on pseudoexpertise, built on relevant empirical and theoretical approaches to cultural cognition. We provide exploratory answers to three questions: why is there pseudoexpertise at all; how can pseudoexperts be successful despite not being experts; and what becomes of pseudoexperts in the long run. Together, these conceptual and theoretical approaches to pseudoexpertise draw a preliminary framework from which to approach the very troubling problem posed by persons usurping the capacities and reputations of genuine experts.

The shortlist effect: nestedness contributions as a tool to explain cultural success

Detecting the forces behind the success or failure of cultural products, such as books or films, remains a challenge. Three such forces are drift, context-biased selection and selection based on content - when things succeed because of their intrinsic appeal. We propose a tool to study content-biased selection in sets of cultural collections - e.g. libraries or movie collections - based on the 'shortlist effect': the fact that smaller collections are more selective and more likely to favour highly appealing items over others. We use a model to show that, when the shortlist effect is at work, content-biased cultural selection is associated with greater nestedness in sets of collections. Having established empirically the existence of the shortlist effect, and of content-biased selection, in 28 sets of movie collections, we show that nestedness contributions can be used to estimate to what extent specific movies owe their success to their intrinsic properties. This method can be used in a wide range of datasets to detect the items that owe their success to their intrinsic appeal, as opposed to 'hidden gems' or 'accidental hits'.