Age has been considered as one of the most salient determinants that modulate social influence. Early pioneering research focused on the negative impacts of peers on adolescents' behavior. A seminal work by Gardner and Steinberg (10) showed that adolescents, compared to adults and young adults, take more risks when in peer groups. Adolescents' increased risk-seeking behavior was accounted for by the imbalance between adolescents' reward and cognitive control circuits (52, 53). In line with this neurodevelopmental model, their heightened social susceptibility was suggested to be associated with socio-emotional neural system (54, 55). Supporting these neural sensitivity models for adolescents, adolescents who exhibited increased risk-taking choices under the presence of peers indeed showed increased BOLD responses in the reward circuit, including the ventral striatum and orbitofrontal cortex (12).

In contrast to classic studies on social influence in adolescents, recent studies gave more attention to positive impacts of social influence (56). Do et al. (57) specifically compared adolescents' conforming behaviors toward different types of social influence. In this study, adolescents tended to stick to their original attitudes toward various types of behaviors, but on the cases when they change their attitudes, adolescents conformed to constructive behaviors (e.g., working hard in school) more than unconstructive behaviors (e.g., smoking a cigarette). Another study used computational modeling approach and showed neural and behavioral evidence for positive peer influence in adolescents (20). Adolescents were making a series of gamble choices and presented with social others' choices before they made each choice. Consistent with the results observed in adults (17), adolescents followed others' choices on average, and such conformity was explained by added social value to the option others chose. In particular, adolescents who never used any types of substances were influenced by others' safe choices, whereas adolescents who have used were not. Although these studies did not directly compare adolescents' decision patterns from those of adults, the results suggested the mechanisms how individuals use social information in their adolescence, a sensitive period for sociocultural processing (6).

Considering the hormonal effects on biological development of the brain, one should consider pubertal stage as a determinant as important as age in developmental research. Indeed, across many adolescent studies, it has been reported that the extent to which individuals are susceptible to social influence is heightened during adolescence and usually diminished after pubertal growth (55, 58, 59). Moreover, recent functional neuroimaging studies suggested that puberty might play a more important role than chronical age in structural and functional development of the brain [(60); for review, see (61)]. This set of studies again highlights that individuals' age would explain considerable variability in their neural and behavioral patterns reflecting individual differences in social information processing.

Another noteworthy demographic factor is socioeconomic status (SES). There have been fairly consistent results suggesting that individuals' socioeconomic status has a significant effect on their behavior in social context. Psychological research suggested the association between individuals' social class and their perspectives over the social environmental (62). Specifically, individuals' high and low classes were considered to be shaped by abundance (or scarcity) of available resources, which in turn may underlie their behavioral tendencies either to focus on one's own internal states or to external factors (62). Consistent with this view, empirical research on social influence among marginalized groups also reported that they tend to conform to their peers more not to be excluded from their community and assert their identity in the group (63).

Recent neuroimaging research further supported the role of SES in individuals susceptibility to social influence. Casio et al. (64) examined whether individuals' SES moderates the relationship between brain responses to social exclusion and the extent to which they conform to peer influence. Specifically, individuals who had low SES showed positive association between neural sensitivity to social exclusion measured in the “social pain” network regions [including dorsal anterior cingulate cortex (dACC), anterior insula, and subgenual cingulate cortex (subACC)] and their conforming tendencies, whereas individuals who had high SES showed the opposite association. Comparable moderating effects of SES were observed for the brain regions implicated in mentalizing [e.g., medial prefrontal cortex (mPFC), temporoparietal junction (TPJ)] (64, 65). These results together imply that SES is neurocognitively linked to the way people process social information.

Of note, the measurements of SES vary across studies and these results should be interpreted with caution. The most common indices include income and educational levels (64, 66), and subjective assessments, such as perceived neighborhood quality (67) and the MacArthur ladder, which measures individual belief about one's location in a status order (65). Although these assessments are usually correlated, they should not be used interchangeably, because they might have enough differential effects on the brain development (68).

Among individuals who have the same demographic profiles, social influence still may have very different impacts, contingent upon individuals' psychological characteristics. Given the social characteristic of the information processing, social anxiety is one of the closest psychological factors that may modulate the effect of social influence. A recent study reported that individuals' social anxiety was positively associated with their conformity to bullying under social influence, such that individuals who show highest social anxiety level conforms to others the most (69). Even in learning directly from experience, highly anxious individuals showed a negative bias (i.e., learning better from bad news) when social others were observing (70). Another study examined social influence differences between healthy individuals and individuals with social anxiety disorder (71). Consistent with the results from the subclinical population, individuals with social anxiety disorder showed higher susceptibility to social influence particularly when social others rated presented face as more attractive than they originally reported. This result was interpreted as evidence for increased motivation to pursue social acceptance and avoid social rejecting in individuals with high social anxiety.

Self-esteem is another psychological characteristic that may be associated with the extent to which one is swayed by others' opinion. Indeed, various classic social psychology research have examined whether individuals' self-esteem is a major moderator of social influence (72–74). Despite the general results showcasing negative association with individuals' susceptibility to peer influence—individuals with low self-esteem are more susceptible to others' influence (72, 74)—, other studies suggested that the relationship is rather more complex. Nisbett and Gordon (73) suggested that modulating effect of self-esteem may differ depding on the type of social influence. Particularly, individuals' self-esteem was negatively associated with the extent to which they are influenced by others for the type of social influence that is relatively easy to comprehend but implausible, while the association was non-monotonic or even opposite for a difficult but plausible message.

Recent neuroimaging studies corroborated this suggested association between self-esteem and their susceptibility to social information. Somerville et al. (75) reported that individuals who had low self-esteem not only reported that they received positive feedbacks less from others, but also were more sensitive to positive feedbacks received by others compared with individuals who had high self-esteem. This result implied that social feedbacks might be exaggerated in low self-esteem individuals, and thus have increased susceptibility to social influence. Will and colleagues (76) used computational modeling approach and suggested that individuals' self-esteem is established through the way how they learn about social others. These results altogether hint a possibility that self-esteem is more than a modulator for individuals' social susceptibility, but rather a dynamically changing characteristic shaped by the history of social interactions.

We reviewed various individual characteristics that are associated with the extent to which individuals are influenced by social contexts. As introduced above, vast amount of studies showed that a large variance of individual differences exists in susceptibility to social influence. However, only few studies directly took these associated factors into account in constructing a cohesive computational model of social influence. Individual characteristics such as age and socioeconomic status may be closely tied to developmental changes or differential learning experiences, while other characteristics (e.g., anxiety and self-esteem) may be linked to baseline traits each individual has and to a specific state individuals reside at the moment. Better mechanistic understanding of social influence spanning across these individual characteristics may provide explanation why minorities who are most vulnerable (e.g., adolescents), or marginalized and stigmatized cohorts are more susceptible to their social environment (3, 12) and even likely to experience mental health problems (77, 78).

When one has a chance to decide on the team members to work together, one would usually prefer others who he or she shares similar perspectives and relates one another easily. A biased behavioral tendency of being assorted based on individuals' preference is often observed in social context, such that individuals who are closer in their social network are more likely to have similar preference (79). Moreover, social closeness, a psychological construct that is well-described as a shared variance between oneself and others (80), was shown to have a significant effect on individuals' judgement about others (81). In other psychology studies where a dichotomous classification of social relationship is adopted (in- vs. out- group) showed consistent results, such that individuals showed a biased preference toward in-group members (82). Such biases toward socially intimate others might be accounted for by their motivation to keep their membership stable and to enhance self-esteem (2).

Recent neuroimaging studies presented further evidence explaining why and how such biases exist. Sip et al. (83) examined whether social feedbacks from a gender-matched close friend vs. from a confederate have differential impacts on individuals' decision pattern and on their neural responses. Individuals were responsive to social feedback and showed changes in choice patterns accordingly, but only when the feedback came from a close friend. This effect was reflected in BOLD responses in the vmPFC and posterior cingulate cortex (PCC), which they presented as supporting evidence for modulatory impact of social closeness on decision-making processes. A similar study that examined individuals' neural responses to social influence revealed differences when the influence originated from in- vs. out- group (84). Particularly, a set of brain regions including the medial prefrontal cortex (mPFC), amygdala, and ventral striatum (vStr) showed higher BOLD responses for the social influence from in-group than out-group members. Consistent with these findings, the default mode network (85), a set of brain regions including the medial PFC and PCC, and its interaction with subcortical regions are known to be closely associated with mental representation about self-other relationship (86). These studies together highlight that social closeness is an important determinant for social information processing.

Another very closely related factor is whether the achieved social information is perceived useful or not. When expertise of social others is explicitly informed, one can use this knowledge to judge whether social information from them is reliable or not. Supporting this view, various studies have shown that people tend to follow opinion and advice from people with expertise than from novice (87, 88). Klucharev et al. (89) suggested that presenting an object paired with an expert enhances memory performance and moreover has a positive impact on the attitude toward the object. Such an impact of perceived expertise was associated with re-evaluation of an item (89, 90), which may account for the reason why people are more likely to follow experts' opinion.

It is important to note that in most of the cases, it is not obvious whether the social information is useful or not. Thus, individuals should estimate how useful the social information is to maximize one's own benefit (or minimize the harm). As crude heuristics, opinion from larger group of people can be taken into account more heavily (45), and others' faster responses are considered more informative (91). Independent of the true usefulness of the information, individuals were more likely to be persuaded by others when presented with higher confidence (92, 93). Evaluation of the confidence that is presented for (or estimated to be associated with) the social information was tracked in the vmPFC, an area dissociable from the region that encoded subjective value signal combining one's own and others' preference (44, 94). These results support the view that by estimating who knows better or whether the social information is useful, individuals can choose their strategy to learn from social others (13, 95).

When being around social others, there are different ways to acquire additional social information. The type of information one can achieve is yoked to the methods how social influence is acquired, and thus how one processes and uses the information naturally should be different accordingly. The most direct way to acquire social information is through a chance to observe others' choices which inform others' preferences and social norms. Chung et al. (17) showed that individuals tend to follow others' choices during risky decision-making. By conducting a formal model comparison, they suggested that such conformity is explained by a value-based decision process combining additional utility to the option chosen by others, rather than by changing individuals' original preferences. The mechanisms how individuals combine their own knowledge and preference with social information may vary. Individuals may project their own preference in predicting that of others (96), and also track whether others' intentions underlying the observed actions of others change over time (97). Other studies suggested that individuals use social information to adjust their own opinion and intend to match with that of others. Specifically, when individuals were asked to report attractiveness of a series of faces after viewing others' responses, their original attractiveness reports were adjusted toward the others (40, 98). These results suggested that individuals are able to track the difference of the values (or preference) between their own and others (17, 40, 41), and change their choices (or ratings) accordingly to minimize the difference (40).

On other occasions, one can be mindful of being around others, but have no chance to directly observe others' choices. The impact of simple presence of others is largely investigated in adolescents, where presence of friends were found to increase adolescents' risk seeking behavior (10, 12, 99). Individuals tended to show higher sensitivity to rewards and more impulsive choices under presence of others even if the social others were not friends, but strangers (100). Such social influence was attributed to social reward, associated with approval from others (101). In a recent study, Powers et al. (102) also examined impacts of the contexts where friends were simply present at the same room or monitoring participants' choices. Particularly, options were more likely to be chosen when they were paired with friends' monetary gains compared with when they were paired with friends' losses. In adults, such adjustment of individuals' choice attitudes were more pronounced when friends were monitoring the choices than merely present, while adolescents showed comparable responses to the social contexts regardless of whether friends could witness the choices or not. These results suggested that individuals may take into account wellbeing of friends, particularly when others can immediately witness the choices.

Individuals may infer what others would expect from their choices and place social values toward meeting the inferred expectation (13, 46). This perspective was closely examined in a recent study where participants were asked to predict others' choices (19). After successfully learning others' choices, individuals' preferences for risky choices changed toward that of others as if there was a “behavioral contagion”. The main goal of predicting others' choices might have motivated individuals to simulate others' preferences and mentalize (103), which may underlie why social context affects individuals differently.

We reviewed that how social influence is conveyed may shape the mechanism how a social context would affect individuals' choices. When individuals are under a social context, they may start extracting a set of information ranging from whether others share the same goal as them to whether others have more amount of information. In the inference process figuring out social others' goals, individuals may recalibrate their subgoals [e.g., to collaborate or compete with others, to mimic others' actions (104), to meet a consensus (105)]. Given that real world is largely uncertain and volatile, we, as social agents, must be constantly solving such an inference problem to first evaluate the usefulness of social information and next alternate how to use the information (46).

Social influence can be readily observed in almost every kind of decision process in our life. Mirroring this, there were many empirical studies ranging from the simplest perceptual decision-making to complex moral decision-making where they used a variety of task paradigms to show the effects of social influence on human information processing. Perceptual decision-making tasks are based on the evaluation of sensory information, such as the length of lines (106), the dominant color of the presented patches (107), or the shape of three-dimensional objects (108). Personal preference tasks include variety of options, such as preference for t-shirts (41), faces (40, 98), and works of art (108, 109). In monetary reward tasks, there are explicit gains and losses of money associated with each of the choice option (17, 19, 110). Lastly, in social preference tasks, individuals encounter decision-making situation where they have to consider explicit losses and gains of social others and their own simultaneously (29, 101). On average, behavioral changes indeed were observed under social influence across all of these studies that probe different levels of cognitive processing in humans. However, due to the variety of contexts each study adopted (e.g., cover stories) and the differences in the targeted cognitive processes (e.g., perception, valuation), there is no universal computational framework that explains the mechanism of social influence across domains.

There are a few computational frameworks that provided cross-domain accounts for social influence (21, 22). First, individuals may be trying to learn others' preferences and values under social influence. Such “normative influence” of social contexts, where social others' choices are not necessarily based on a better set of information, were explained by reinforcement learning (RL) framework capturing individuals' change of behaviors toward others [(40, 98), c.f., (111)]. Consistent with this perspective, individuals under social context were sensitive to the opinion differences between them and the others (41, 112), and it was shown that a set of brain regions involved in social and monetary reward learning overlap (113, 114). The RL framework successfully captured the extent to which individuals conform to others' preference-based choices over primary and social rewards (40, 115). Second, individuals may be collecting more information from others' choices. Following such “informational influence” of social contexts, individuals seemed to be using others' responses and choices to appropriately adjust their original responses. To integrate information from two sources, individuals computed the importance and reliability of each piece of information (44, 45, 47). Such a Bayesian learner framework successfully explained individuals' conformity not only in perceptual, but also in value-based decision-making particularly when statistical inference was available.

It is worth noting that behavioral patterns which are well-explained by the same computational framework may in fact induced by different neural mechanisms; differential implementation level explanation as per Marr's three levels of analysis (116). For example, a recent study directly compared multivoxel neural patterns for social conformity with that for classic reward learning, and suggested that neural responses in the brain regions typically involved in non-social RL (e.g., striatum) do not explain whether or not individuals conform to social information (111). This emphasizes again the importance of interdisciplinary approaches in understanding human information processing. A careful consideration of specific contexts will shape individuals' motivation (“computation level”), but why and how individuals process social information in the context need thorough examination not only in algorithmic level (e.g., computational modeling) but also in implementational level (e.g., functional neuroimging) (117).

We briefly reviewed plausible mechanisms suggested to date of social influence over different decision domains. Although cognitive motivations defined over psychological constructs including value and information maximization accounted for neural and behavioral mechanisms under social influence (33), applying the same mechanism to different levels of cognitive processing has been challenging, because task settings (e.g., goal, order, amount of information) also varied across different studies. Future studies may tailor the study design to specifically examine individuals' cross-domain susceptibility to social information. By using the same task settings, but over different domain, we would get a direct chance to address whether individuals' domain-specific sensitivity and confidence, which will be manifested as preference for social information, affect the extent to which individuals use social information.