Social Inference Research Articles

Social meaning and pragmatic reasoning: The case of (im)precision

On the basis of a speaker's choice between linguistic alternatives, a hearer can draw inferences not only about facts of the world, but also about the social properties of the speaker. The goal of this work is to investigate how such social meanings arise, particularly in the case where the alternatives in question differ in their core logical or semantic meaning. Taking variation in numerical precision level as a case study, we seek to test the broad general hypothesis that social inferences may be derived via pragmatic reasoning about the needs of the situation, the epistemic state of the speaker, and the reasons for their choice of form. We report on two matched guise studies which demonstrate that the social meaning of (im)precision is sensitive to context and (to some extent) speaker knowledge state, and are correlated with inferred reasons for expression choice, findings which support the predictions of the pragmatic view.

Effectiveness of a social cognition remediation intervention for patients with schizophrenia: a randomized-controlled study

This randomized-controlled study evaluates the effectiveness of a newly developed social cognition rehabilitation intervention, the modified Social Cognition Individualized Activity Lab (mSoCIAL), in improving social cognition and clinical and functional outcomes of persons with schizophrenia recruited in two Italian sites: University of Campania “Luigi Vanvitelli” in Naples and ASST Fatebenefratelli-Sacco in Milan. mSoCIAL consists of a social cognitive training module focusing on different domains of social cognition and of a narrative enhancement module. We assessed changes in social cognition, clinical characteristics and functional variables in patients with schizophrenia who participated in 10 weekly sessions of mSoCIAL or received treatment as usual (TAU). A paired-sample t test and a repeated-measures MANOVA were used to investigate respectively within and between-group differences. Twenty people with schizophrenia were blindly assigned to mSoCIAL and 20 to TAU. After 10 weeks, mSoCIAL significantly improved disorganization, emotion recognition, functional capacity and real-life functioning. As compared to TAU, the mSoCIAL group showed a significant improvement in minimal and enriched social inference domain of theory of mind, and in key domains of real-life functioning (interpersonal relationships, everyday life skills, and work skills). mSoCIAL improved social cognition and real-life functioning of people with schizophrenia. These results highlight the importance of social cognition deficit treatment in schizophrenia and the necessity for these interventions to be multifaced and personalized. Such an approach ensures that improvements in social cognition translate into enhanced functional outcomes.Trial registration NCT05130853, registered on 24 November 2021.

Domain-specific representation of social inference by neurons in the human amygdala and hippocampus.

Inferring the intentions and emotions of others from behavior is crucial for social cognition. While neuroimaging studies have identified brain regions involved in social inference, it remains unknown whether performing social inference is an abstract computation that generalizes across different stimulus categories or is specific to certain stimulus domain. We recorded single-neuron activity from the medial temporal lobe (MTL) and the medial frontal cortex (MFC) in neurosurgical patients performing different types of inferences from images of faces, hands, and natural scenes. Our findings indicate distinct neuron populations in both regions encoding inference type for social (faces, hands) and nonsocial (scenes) stimuli, while stimulus category was itself represented in a task-general manner. Uniquely in the MTL, social inference type was represented by separate subsets of neurons for faces and hands, suggesting a domain-specific representation. These results reveal evidence for specialized social inference processes in the MTL, in which inference representations were entangled with stimulus type as expected from a domain-specific process.

Infants' Expectations for Helping in Imitators.

Human infants seem to make positive social inferences about individuals who imitate others. In three preregistered experiments we test if these inferences include an expectation that imitators will be helpful, and also ask if the inferences infants make are about imitators' dispositions or primarily about their relationships. In each experiment 8- to 9-month-old infants saw one individual imitate, and another individual not imitate, the same target social partner. When the imitator and non-imitator had the opportunity to help the target individual they had previously interacted with, infants looked longer when the non-imitator helped than when the imitator helped. However, when the potential recipient of help was a new social partner, infants' looking did not differ when the imitator or non-imitator helped. Overall, these results support the hypothesis that infants perceive imitation as prosocial or affiliative and thus expect imitators to be helpful. However, these expectations are limited to inferences about a specific prosocial relationship between the imitator and their target.

Age Differences in Mental State Inference of Sarcasm: Contributions of Facial Emotion Recognition and Cognitive Performance.

Older age is associated with poorer ability to accurately infer mental states, but some mental states are more complex than others. Sarcasm is a complex mental state because the literal and intended meaning of a speaker's words are in opposition. Individuals must rely on additional cues (e.g., facial expressions, intonation) for accurate inference. We hypothesized that understanding of sarcastic versus sincere exchanges would be more sensitive to age-related difficulty in mental state understanding. We examined accuracy at identifying sarcasm among 263 adults (ages 18-90 years) using videos of social interactions in The Awareness of Social Inference Test. Hypotheses were tested using a logistic linear mixed effects model predicting correct/incorrect trial-level responses. To characterize why sarcasm differed with age, we measured 2 abilities commonly implicated in mental state understanding: facial emotion recognition and cognitive performance. Sarcasm understanding declined with age, whereas understanding of sincere exchanges did not. Both better emotion recognition and cognitive performance related to better understanding of sarcastic but not sincere exchanges. Only cognitive performance showed an age-related effect such that the cognitive performance among the oldest participants facilitated their understanding of both sarcastic and sincere exchanges. We showed that individual variation related to age and social and cognitive performance is more pronounced when the use of multiple mental state cues is more (sarcasm) or less (sincerity) necessary for accurate understanding of social interactions. Naturalistic paradigms involving multiple mental state cues can address important questions about how older adults make decisions in the real world.

Are you what you emoji? How skin tone emojis and profile pictures shape attention and social inference processing

Emojis can express emotions and some aspects of the sender’s identity; however, only limited research has explored how the choice of skin tone in emojis influences the perceptions of the users. We examined the interaction between emoji skin tones and profile pictures in instant messaging, using self-reported and eye tracking measures. White participants viewed 14 screenshots of conversations (9 target and 5 fillers) where the sender used an emoji in a Darker or Lighter skin tone, or the default Yellow; alongside profile pictures displaying a Black or White individual, or a landscape as a neutral condition. Results showed that Black senders using Darker emojis were seen as warmer and closer to the receiver, but less competent, suggesting a dimensional compensation effect. Conversely, Black senders using Lighter emojis appeared more competent, but less warm. In the Neutral condition, Lighter emojis improved warmth and relationship quality, but reduced competence inferences, unlike Yellow and Darker emojis, suggesting a black sheep effect (in-group strictness). Yellow emojis were assumed to be sent by White individuals. Eye-tracking measures revealed an implicit bias towards White senders using Darker emojis, although such an impact was not observed for Black senders using Lighter emojis. Overall, findings indicate that skin tone emojis and profile pictures influence sender perception and challenge the neutrality of Yellow emojis.

Social cognition and healthy aging: Cross-sectional associations of emotion perception, theory of mind, and emotional empathy.

Older adults are identified to have reduced social cognitive performance compared to younger adults. However, few studies have examined age-associations throughout later life to determine whether these reductions continue with advancing age. This study assesses cross-sectional associations of emotion perception, cognitive and affective theory of mind (ToM), and emotional empathy in a healthy sample of 157 adults aged 50-89 years (M = 65.31, SD = 9.00, 68% female sex). Emotion perception, cognitive ToM, and affective ToM were measured using The Awareness of Social Inference Test Short Form (TASIT-S), while affective ToM was also measured using Reading the Mind in the Eyes Revised (RME-R). Emotional empathy was measured using the Empathy Quotient. Multiple regression analyses, adjusting for multiple comparisons, revealed a moderate negative association between age and emotion perception for all emotions combined, as well as for sad and revolted expressions, but not happy, neutral, anxious, or angry expressions. Age had a negative, moderate association with first-order cognitive, second-order cognitive, and affective ToM measured using TASIT-S, but not RME-R. Age was not significantly associated with emotional empathy. This study contributes to the limited understanding of age-related associations of social cognitive performance throughout later life. This knowledge can inform future research examining the clinical utility of including social cognitive measures in neuropsychological screening and diagnostic tools for later-life neurological disorders.

Investigating the neural computations underlying visual social inference with graph neural network and inverse planning models

Investigating the neural computations underlying visual social inference with graph neural network and inverse planning models

Disentangling the effects of similarity, familiarity, and liking on social inference strategies.

People constantly make inferences about others' beliefs and preferences. People can draw on various sources of information to make these inferences, including stereotypes, self-knowledge, and target-specific knowledge. What leads people to use each of these sources of information over others? The current study examined factors that influence the use of these sources of information, focusing on three interpersonal dimensions - the extent to which people feel (a) familiar with, (b) similar to, or (c) like the target. In four studies (total N = 1136), participants inferred the beliefs and preferences of others - celebrities (Studies 1a-1b), constructed fictional targets (Study 2), and actual acquaintances (Study 3). Participants also rated familiarity with, similarity to, and liking of the target. Analyses assessed the use of each source of information by comparing inferences with information provided by those sources. Familiarity was associated with greater use of target-specific knowledge, while similarity and liking were associated with self-knowledge. Low similarity and high liking were associated with increased use of stereotypes. We discuss the implication of these findings and their applicability to unique cases, including inferences about celebrities, public figures, and positively stereotyped groups, in which familiarity, similarity, and liking do not perfectly align.

Individual differences in autism-like traits are associated with reduced goal emulation in a computational model of observational learning.

One's ability to infer the goals and intentions of others is crucial for social interactions, and such social capabilities are broadly distributed across individuals. Autism-like traits (i.e., traits associated with autism spectrum disorder (ASD)) have been associated with reduced social inference, yet the underlying computational principles and social cognitive processes are not well characterized. Here we tackle this problem by investigating inference during social learning through computational modeling in two large cross-sectional samples of adult participants from the general population (N1=943, N2=352). Autism-like traits were extracted and isolated from other associated symptom dimensions through a factor analysis of the Social Responsiveness Scale. Participants completed an observational learning task that allowed quantifying the tradeoff between two social learning strategies: imitation (repeat the observed partner's most recent action) and emulation (infer the observed partner's goal). Autism-like traits were associated with reduced observational learning specifically through reduced emulation (but not imitation), revealing difficulties in social goal inference. This association held even when controlling for other model parameters (e.g., decision noise, heuristics), and was specifically related to social difficulties in autism but not social anxiety. The findings, replicated in an additional sample, provide a powerfully specific mechanistic hypothesis for social learning challenges in ASD, employing a computational psychiatry approach that could be applied to other disorders.

The effect of foreigner talk on children’s evaluations of addressees

Children evaluate others based on how they speak, but do children evaluate others based on how they are spoken to? We examined how U.S. children and adults (N = 170 5- to 10-year-olds, 49 % female; 107 adults; in a city with a foreign population of 17.9 %) evaluated addressees of Foreigner Talk (i.e., slow, loud, simplified speech). In Study 1, children and adults evaluated Foreigner Talk addressees more negatively than Peer Talk or Teacher Talk addressees. In Study 2, adults and older children incorporated Foreigner Talk with additional contextual cues to inform their evaluations: a local peer receiving Foreigner Talk received lower evaluations than a foreign peer receiving Foreigner Talk. With medium to large effect sizes, these studies indicate the importance of speech register in children’s social inferences.

Factors related to social inferencing performance in moderate-severe, chronic TBI

ABSTRACT Objective Following traumatic brain injury (TBI), deficits in social cognition are common. Social inferencing is a crucial component of social cognition that enables an individual to understand the thoughts, feelings, and intentions of a communication partner when this information is not explicitly stated. Existing literature suggests a variety of factors contribute to social inferencing success (e.g. biological sex, executive functioning), yet findings are not conclusive, largely because these factors have been examined in isolation. Method In this cross-sectional study, stepwise regression with cross validation was used to examine the extent that several theoretically motivated factors were associated with social inferencing (measured by performance on The Awareness of Social Inference Test [TASIT]) in adult participants with TBI (n = 105). Demographic information, executive functioning, aggression, emotional functioning measures, and participation in society were all examined in relation to social inferencing performance. Results The findings confirm the importance of higher-level cognitive skills (i.e. executive functioning) in social inferencing, and advance the literature by underlining the potential importance of productive participation in social inferencing performance. Conclusion This study innovatively highlights factors linked with social inferencing skills and, in doing so, how deficits in social inferencing might manifest in the lives of individuals with TBI.

Imaginative elaboration in agenesis of the corpus callosum: topic modeling and perplexity.

Previous studies have found deficits in imaginative elaboration and social inference to be associated with agenesis of the corpus callosum (ACC; Renteria-Vasquez et al., 2022; Turk et al., 2009). In the current study, Thematic Apperception Test (TAT) responses from a neurotypical control group and a group of individuals with ACC were used to further study the capacity for imaginative elaboration and story coherence. Topic modeling was employed utilizing Latent Diritchlet Allocation to characterize the narrative responses to the pictures used in the TAT. A measure of the difference between models (perplexity) was used to compare the topics of the responses of individual participants to the common core model derived from the responses of the control group. Story coherence was tested using sentence-to-sentence Latent Semantic Analysis. Group differences in perplexity were statistically significant overall, and for each card individually (p < .001). There were no differences between the groups in story coherence. TAT narratives from persons with ACC were normally coherent, but more conventional (i.e., more similar to the core text) compared to those of neurotypical controls. Individuals with ACC can make conventional social inferences about socially ambiguous stimuli, but are restricted in their imaginative elaborations, resulting in less topical variability (lower perplexity values) compared to neurotypical controls.

D2/D3 dopamine supports the precision of mental state inferences and self-relevance of joint social outcomes

Striatal dopamine is important in paranoid attributions, although its computational role in social inference remains elusive. We employed a simple game-theoretic paradigm and computational model of intentional attributions to investigate the effects of dopamine D2/D3 antagonism on ongoing mental state inference following social outcomes. Haloperidol, compared with the placebo, enhanced the impact of partner behaviour on beliefs about the harmful intent of partners, and increased learning from recent encounters. These alterations caused substantial changes to model covariation and negative correlations between self-interest and harmful intent attributions. Our findings suggest that haloperidol improves belief flexibility about others and simultaneously reduces the self-relevance of social observations. Our results may reflect the role of D2/D3 dopamine in supporting self-relevant mentalising. Our data and model bridge theory between general and social accounts of value representation. We demonstrate initial evidence for the sensitivity of our model and short social paradigm to drug intervention and clinical dimensions, allowing distinctions between mechanisms that operate across traits and states.

A social inference model of idealization and devaluation.

People often form polarized beliefs, imbuing objects (e.g., themselves or others) with unambiguously positive or negative qualities. In clinical settings, this is referred to as dichotomous thinking or "splitting" and is a feature of several psychiatric disorders. Here, we introduce a Bayesian model of splitting that parameterizes a tendency to rigidly categorize objects as either entirely "Bad" or "Good," rather than to flexibly learn dispositions along a continuous scale. Distinct from the previous descriptive theories, the model makes quantitative predictions about how dichotomous beliefs emerge and are updated in light of new information. Specifically, the model addresses how splitting is context-dependent, yet exhibits stability across time. A key model feature is that phases of devaluation and/or idealization are consolidated by rationally attributing counter-evidence to external factors. For example, when another person is idealized, their less-than-perfect behavior is attributed to unfavorable external circumstances. However, sufficient counter-evidence can trigger switches of polarity, producing bistable dynamics. We show that the model can be fitted to empirical data, to measure individual susceptibility to relational instability. For example, we find that a latent categorical belief that others are "Good" accounts for less changeable, and more certain, character impressions of benevolent as opposed to malevolent others among healthy participants. By comparison, character impressions made by participants with borderline personality disorder reveal significantly higher and more symmetric splitting. The generative framework proposed invites applications for modeling oscillatory relational and affective dynamics in psychotherapeutic contexts. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Social Implications of In Vitro Fertilisation (IVF) on Women in India

In vitro fertilisation (IVF) is a technological innovation enabling infertile women to conceive through medical procedures. However, social inferences of IVF need to be contextualised within gender dynamics, especially in India. Though several studies have examined specific social aspects of IVF none have delineated the combination of determinants as well as implications of IVF for women. The present study assesses various social factors influencing choices for infertility treatments like IVF, and also the implications for women undergoing IVF. For a nuanced understanding of these conditions in the larger social context of India, 41 studies discussing important indices like gender dynamics, health status, power relations and social vulnerabilities of women experiencing IVF have been critically reviewed. Based on the review we contend that social pressures, gender identity, desire for a biological child, fear of marital discord and loss of self-esteem are most important factors determining such decisions.

Neural Amortized Inference for Nested Multi-Agent Reasoning

Multi-agent interactions, such as communication, teaching, and bluffing, often rely on higher-order social inference, i.e., understanding how others infer oneself. Such intricate reasoning can be effectively modeled through nested multi-agent reasoning. Nonetheless, the computational complexity escalates exponentially with each level of reasoning, posing a significant challenge. However, humans effortlessly perform complex social inferences as part of their daily lives. To bridge the gap between human-like inference capabilities and computational limitations, we propose a novel approach: leveraging neural networks to amortize high-order social inference, thereby expediting nested multi-agent reasoning. We evaluate our method in two challenging multi-agent interaction domains. The experimental results demonstrate that our method is computationally efficient while exhibiting minimal degradation in accuracy.

Sharing luxury consumption on social media platforms: Motive inferences and downstream consequences

AbstractIndividuals are increasingly sharing their consumption activities on social media platforms. However, the inferences people draw from consumption posts are understudied. Three studies showed that observers infer more self‐presentational motives and less self‐expressive motives when they see others post their luxury (vs. nonluxury) consumption on social media. The attributions of more self‐presentational motives and less self‐expressive motives lead observers to perceive the poster as inauthentic and undermine the observers' interpersonal interest in the poster. The negative effects of posting luxury consumption are attenuated when the post content emphasizes competencies (vs. wealth). This work contributes theoretically to the research on self, signaling, and social inferences. The current findings have practical implications for social media users and marketers of luxury products.

Social System Inference From Noisy Observations

This article studies social system inference from a single noisy trajectory of public evolving opinions, wherein observation noise leads to the statistical dependence of samples on time and coordinates. We first propose a cyber-social system that comprises individuals in a social network and a set of information sources in a cyber layer, whose opinion dynamics explicitly takes the asymmetric cognitive bias including confirmation bias and negativity bias and the process noise into account. Based on the proposed cyber-social model, we then study the sample complexity of least-square auto-regressive model estimation, which governs the length of a single observed trajectory that is sufficient for the identified model to achieve the prescribed levels of accuracy and confidence (PAC). Building on the identified social model, we then investigate social inference, with a particular focus on the weighted network topology and the model parameters of asymmetric cognitive bias. Finally, the theoretical results and the effectiveness of the proposed inference framework are validated by the U.S. Senate Member Ideology data.

Policy of Islamic Family Law in Textual and Historical Approach

The policy of family law in Indonesia is based on principles stipulated in the Civil Code (Kitab Undang-Undang Hukum Perdata or KUHPerdata) and several other laws that regulate marriage, divorce, children’s rights, and joint property in marriage. In formulating policies, a classic approach has been traditionally used. This research employs a library method, which involves collecting relevant texts and manuscripts for analysis and conclusions. The following are some important family law policies in Indonesia: marriage, divorce, children’s rights, and joint property in marriage. Fiqh not only faces difficulties in resolving various social problems and issues but also struggles in defining itself, particularly in the context of formulating legal methods to address these problems. As an initial step toward reconstructing fiqh, this article attempts to propose a solution in fiqh methodology, namely a unified approach to Shari’ah and social inference. In essence, this method aims to bridge and “integrate” the textual (normative) and contextual (historical-empirical) approaches simultaneously within an “Islamic” scientific research model. The offered conclusion is that both textual and historical approaches are crucial in formulating policies of Islamic family law. Keywords: policy, Islamic family law, approach