This paper generalizes the p* class of models for social network data to predict individual-level attributes from network ties. The p* model for social networks permits the modeling of social relationships in terms of particular local relational or network configurations. In this paper we present methods for modeling attribute measures in terms of network ties, and so construct p* models for the patterns of social influence within a network. Attribute variables are included in a directed dependence graph and the Hammersley-Clifford theorem is employed to derive probability models whose parameters can be estimated using maximum pseudo-likelihood. The models are compared to existing network effects models. They can be interpreted in terms of public or private social influence phenomena within groups. The models are illustrated by an empirical example involving a training course, with trainees' reactions to aspects of the course found to relate to those of their network partners.

We experimentally study intention-based social influence in standard and modified Ultimatum and Impunity games. Standard games with bi-dimensional strategy vectors let individuals decide independently in the role of proposer and responder and allow fairness intentions to be role dependent. Uni-dimensional strategy vectors in modified games constrain individuals to consistent offers and acceptance thresholds. To induce social influence, we randomly match participants in groups of four, which are minimally identified by colors. Social influence is assessed by how one reacts to information about median group intention(s). The $2\times 2$ factorial experimental design varies the order of the two game types and the strategy vector dimensionality. Social influence, depending on the game type and strategy dimensionality, significantly impacts participants’ behavior compared to their own intention. At the aggregate level, however, these differences cancel each other out. As there are more constraints on the action space, uni-dimensionality increases strategic concerns.

Social network data represent interactions and relationships among groups of individuals. One aspect of social interaction is social influence, the idea that beliefs or behaviors change as a result of one’s social network. The purpose of this article is to introduce a new model for social influence, the latent space model for influence, which employs latent space positions so that individuals are affected most by those who are “closest” to them in the latent space. We describe this model along with some of the contexts in which it can be used and explore the operating characteristics using a series of simulation studies. We conclude with an example of teacher advice-seeking networks to show that changes in beliefs about teaching mathematics may be attributed to network influence.

Numerous public initiatives aim to influence individual food choices by informing about what is considered ‘healthy’, ‘climate-friendly’, and generally ‘sustainable’ food. However, research suggests that rather than public authorities, social influence is more likely to affect people’s behaviour. Using a randomised controlled trial, this study investigated if and how the two kinds of influences (factual versus social) could affect the real-life, self-reported intake of plant- and animal-based foods. In a four-month randomised controlled trial, a self-selected sample of adults living in Sweden (N = 237) tracked their daily food consumption several times per week using a tailored mobile phone app. Participants were randomised into one of three groups: two treatment groups receiving factual or social information about plant- and animal-based food consumption, or a control group receiving no information. Pre- and post-questionnaires provided additional background information about the participants. Participants’ food habits varied from week to week, and an explorative analysis pointed to a slight decrease in the consumption of animal-based food in the group that received social information. However, the longer-term patterns remained relatively constant in all groups, showing no substantial shift regardless of the kind of cues that the participants received. By investigating the roles of two common types of information about food and dietary change, the results contribute to discussions about how and by whom effective and efficient measures can be implemented to transform food habits. The results suggest there is limited potential for sustained and substantial behavioural changes through both social and factual information campaigns.

We present an opinion dynamics model framework discarding two common assumptions in the literature: (a) that there is direct influence between beliefs of neighboring agents, and (b) that agent belief is static in the absence of social influence. Agents in our framework learn from random experiences which possibly reinforce their belief. Agents determine whether they switch opinions by comparing their belief to a threshold. Subsequently, influence of an alter on an ego is not direct incorporation of the alter’s belief into the ego’s but by adjusting the ego’s decision-making criteria. We provide an instance from the framework in which social influence between agents generalizes majority rules updating. We conduct a sensitivity analysis as well as a pair of experiments concerning heterogeneous population parameters. We conclude that the framework is capable of producing consensus, polarization and fragmentation with only assimilative forces between agents which typically, in other models, lead exclusively to consensus.

In decision making, people may rely on their own information as well as oninformation from external sources, such as family members, peers, or experts.The current study investigated how these types of information are used bycomparing four decision strategies: 1) an internal strategy that relies solelyon own information; 2) an external strategy that relies solely on theinformation from an external source; 3) a sequential strategy that relies oninformation from an external source only after own information is deemedinadequate; 4) an integrative strategy that relies on an integration of bothtypes of information. Of specific interest were individual and developmentaldifferences in strategy use. Strategy use was examined via Bayesian hierarchicalmixture model analysis. A visual decision task was administered to children andyoung adolescents (N=305, ages 9–14). Individual differences but noage-related changes were observed in either decision accuracy or strategy use.The internal strategy was dominant across ages, followed by the integrative andsequential strategy, respectively, while the external strategy was extremelyrare. This suggests a reluctance to rely entirely on information provided byexternal sources. We conclude that there are individual differences but notdevelopmental changes in strategy use pertaining to perceptual decision-makingin 9- through 14-year-olds. Generalizability of these findings is discussed withregard to different forms of social influence and varying perceptions of theexternal source. This study provides stepping stones in better understanding andmodeling decision making processes in the presence of both internal and externalinformation.

Expertise is a reliable cue for accuracy – experts are often correct in their judgments and opinions. However, the opposite is not necessarily the case – ignorant judges are not guaranteed to err. Specifically, in a question with a dichotomous response option, an ignorant responder has a 50% chance of being correct. In five studies, we show that people fail to understand this, and that they overgeneralize a sound heuristic (expertise signals accuracy) to cases where it does not apply (lack of expertise does not imply error). These studies show that people 1) tend to think that the responses of an ignorant person to dichotomous-response questions are more likely to be incorrect than correct, and 2) they tend to respond the opposite of what the ignorant person responded. This research also shows that this bias is at least partially intuitive in nature, as it manifests more clearly in quick gut responses than in slow careful responses. Still, it is not completely corrected upon careful deliberation. Implications are discussed for rationality and epistemic vigilance.

Following up on a recent debate, we examined advice taking in dyads compared to individuals in a set of three studies (total N = 303 dyads and 194 individuals). Our first aim was to test the replicability of an important previous finding, namely that dyads heed advice less than individuals because they feel more confident in the accuracy of their initial judgments. Second, we aimed to explain dyads’ behavior based on three premises: first, that dyads understand that the added value of an outside opinion diminishes when the initial pre-advice judgment is made by two judges rather than one judge (given that the dyad members’ opinions are independent of each other); second, that they fail to recognize when the assumption of independence of opinions does not hold; and third, that the resistance to advice commonly observed in individuals persists in groups but is neither aggravated nor ameliorated by the group context. The results of our studies show consistently that previous findings on advice taking in dyads are replicable. They also support our hypothesis that groups exhibit a general tendency to heed advice less than individuals, irrespective of whether the accuracy of their initial judgments warrants this behavior. Finally, based on the three assumptions mentioned above, we were able to make accurate predictions about advice taking in dyads, prompting us to postulate a general model of advice taking in groups of arbitrary size.

Social influence among people is widely understood to be a universal component of the human experience. However, studies of political behavior have generally approached social influence as specific to a type of behavior, such as voting, in a particular national context. There are good reasons to expect that social influence is observable across diverse behaviors and national contexts. In this study, we test this expectation using a two-wave panel survey of national samples in 19 countries. We employ autoregressive models that address some of the endogeneity challenges associated with attempts to measure social influence with survey designs. Our measure of social influence is predictive of diverse political behaviors in many countries with average effects comparable in size to important standard predictors of behavior.

Historical and comparative social scientists are increasingly interested in explaining the spread of innovations—which social scientists commonly refer to as diffusion and, broadly conceived, can include the spread of new ideas, behaviors, technologies, and institutions. However, in spite of the profusion of studies, researchers do not always specify a diffusion model or its underlying causal mechanisms. Whereas many studies document spatial diffusion, not all specify a vector, model flows of influence and information, or show how people and places are connected (tied) to one another. In reviewing some of the most important work on the spread of religion, violent conflict, and social movements over the last few decades, it is clear to us that social network analysis has revolutionized the historical study of diffusion. Even so, many studies have yet to embrace concepts, methods, and measures from social network analysis. Nevertheless, we are convinced that the combination of historical perspectives on change and innovation, new methods of historical data collection and analysis, and growing sophistication in the application of network concepts and models is shedding light on a host of historical questions and contributing to our general understanding of diffusion.

The paper explains long-term changes in birth, death rates, and in attitude to personal consumption by evolution of preferences by means of cultural transmission. When communities are culturally isolated, they are focused on population growth, which results in large fertility and welfare transfers to children, limited adult consumption, and lack of old-age support. With increasing cultural contact across communities, successful cultural traits induce their hosts to increase their social visibility by limiting fertility and increasing longevity via higher individual consumption. Empirical analysis confirms that social visibility, as measured by the number of language versions of Wikipedia biographical pages, is associated with fewer children and longer lifespan. The presence of notable individuals precedes reduced aggregate birth rates.

Challenging the assumption of perfect legal knowledge, this Article employs social psychology to better understand how individuals make decisions about legal compliance under imperfect information conditions. It adapts the informational aspects of “social influence conception of criminal deterrence” to regulatory compliance at large. However, it conceptualizes social influence as more than just “visible deterrence.” Social Psychology helps us to understand who, how many, and what kind of behaviors constitute adequate social proof to guide an individual’s decision on compliance. Additionally, the interaction of social proof and legal compliance is considered within a dynamic framework in relation to specific rules and across the system. Within this framework, compliance/non-compliance cascades across different rules and can create a perception about legal compliance at large, which in turn guides initial expectations with respect to new laws. Over time, this can create high/low compliance equilibriums within which societies operate. Understanding this informational role that social influence plays in legal compliance can further our understanding of what motivates compliance, the potency of the expressive functions of law in societies operating within different compliance equilibriums, and inform policy discussions on how to improve compliance—both voluntary and through sanction/incentives.