The evaluative information ecology: On the frequency and diversity of “good” and “bad”

More familiar, more credible? Distinguishing two types of familiarity on the truth effect using the drift-diffusion model

Familiar information is more likely to be accepted as true. This illusory truth effect has a tremendous negative impact on misinformation intervention. Previous studies focused on the familiarity from repeated exposure in the laboratory, ignoring preexisting familiarity with real-world misinformation. Over three studies (total N = 337), we investigated the cognitive mechanisms behind the truth biases from these two familiarity sources, and whether fact-checking can curb such biased truth perceptions. Studies 1 and 2 found robust truth effects induced by two sources of familiarity but with different cognitive processes. According to the cognitive process model, repetition-induced familiarity reduced decision prudence. Preexisting familiarity instead enhanced truth-congruent evidence accumulation. Study 3 showed that pre-exposing statements with warning flags eliminated the bias to truth induced by repetition but not that from preexisting familiarity. These repeated statements with warning labels also reduced decision caution. These findings furthered the understanding of how different sources of familiarity affect truth perceptions and undermine the intervention through different cognitive processes.

The Formation of Negative Attitudes Toward Novel Groups

People perceive out-groups, minorities, and novel groups more negatively than in-groups, majorities, and familiar groups. Previous research has argued that such intergroup biases may be caused by the order in which people typically encounter social groups. Groups that are relatively novel to perceivers (e.g., out-groups, minorities) are primarily associated with distinct attributes that differentiate them from familiar groups. Because distinct attributes are typically negative, attitudes toward novel groups are negatively biased. Five experiments (N = 2,615 adults) confirmed the generalizability of the novel groups' disadvantage to different aspects of attitude formation (i.e., evaluations, memory, stereotyping), to cases with more than two groups, and to cases in which groups were majority/minority or in-groups/out-groups. Our findings revealed a remarkably robust influence of learning order in the formation of group attitudes, and they imply that people often perceive novel groups more negatively than they actually are.

Valence-Dependent Implicit Action Generalization Among Group Members

People implicitly generalize the actions of known individuals in a social group to unknown members. However, actions have social goals and evaluative valences, and the extent to which actions with different valences (helpful and harmful) are implicitly generalized among group members remains unclear. We used computer animations to simulate social group actions, where helping and hindering actions were represented by aiding and obstructing another's climb up a hill. Study 1 found that helpful actions are implicitly expected to be shared among members of the same group but not among members of different groups, but no such effect was found for harmful actions. This suggests that helpful actions are more likely than harmful actions to be implicitly generalized to group members. This finding was replicated in Study 2 by increasing the group size from three to five. Study 3 found that the null effect for generalizing harmful actions among group members is not due to the difficulty of detecting action generalization, as both helpful and harmful actions are similarly generalized within particular individuals. Moreover, Study 4 demonstrated that weakening social group information resulted in the absence of implicit generalization for helpful actions, suggesting the specificity of group membership. Study 5 revealed that the generalization of helping actions occurred when actions were performed by multiple group members rather than being repeated by one group member, showing group-based inductive generalization. Overall, these findings support valence-dependent implicit action generalization among group members. This implies that people may possess different knowledge regarding valenced actions on category-based generalization.

Exploring the impact of sentiment on multi-dimensional information dissemination using COVID-19 data in China

The outbreak of information epidemic in crisis events, with the channel effect of social media, has brought severe challenges to global public health. Combining information, users and environment, understanding how emotional information spreads on social media plays a vital role in public opinion governance and affective comfort, preventing mass incidents and stabilizing the network order. Therefore, from the perspective of the information ecology and elaboration likelihood model (ELM), this study conducted a comparative analysis based on two large-scale datasets related to COVID-19 to explore the influence mechanism of sentiment on the forwarding volume, spreading depth and network influence of information dissemination. Based on machine learning and social network methods, topics, sentiments, and network variables are extracted from large-scale text data, and the dissemination characteristics and evolution rules of online public opinions in crisis events are further analyzed. The results show that negative sentiment positively affects the volume, depth, and influence compared with positive sentiment. In addition, information characteristics such as richness, authority, and topic influence moderate the relationship between sentiment and information dissemination. Therefore, the research can build a more comprehensive connection between the emotional reaction of network users and information dissemination and analyze the internal characteristics and evolution trend of online public opinion. Then it can help sentiment management and information release strategy when emergencies occur.

Perceived changes in trait attributions to others and the self

A study was conducted to examine the perceived changes in the impressions of others or self on 133 trait dimensions. Attributions to others were reportedly more negative over time whereas attributions to self were more positive over time. Perceived changes in others' traits appear to be guided by basic behavioral inference processes. Trait beliefs about others tend to be revised when the traits are common and disconfirming behavior is infrequent and more diagnostic. Positive trait impressions of others change more frequently because they are more prevalent and because negative behaviors (that disconfirm positive attributions) are less frequent and more diagnostic than positive behaviors. In contrast, revisions of trait impressions of the self appear to be driven heavily by self-evaluation motivations such as the desire to see self-improvement. The favorableness of changes in trait self-concepts were positively correlated with self-esteem. The consequences of the observed patterns of attributional change for interpersonal relations are discussed.

Are Student Teachers' Overall Expected Emotions Regarding Their Future Life as a Teacher Biased Toward Their Expected Peak Emotions?

Having functional expected emotions regarding one's future life as a teacher is important for student teachers to maintain their motivation to choose a career as a teacher. However, humans show several biases when judging their emotional experiences. One famous bias is the so-called peak-end effect which describes the phenomenon that overall affective judgments do not reflect the average of the involved emotional experiences but the most intense and the most recent of the involved emotional experiences. Regarding student teachers' expected positive emotions, such a bias would be functional since their motivation to become a teacher is enhanced. However, regarding student teachers' expected negative emotions, such a bias would be dysfunctional since their motivation to become a teacher would be decreased. The aim of the present preregistered study was to examine whether student teachers' expected future teaching-related emotions show a peak-end effect. Student teachers viewed 14 common events that could part of a typical everyday routine of a teacher and rated their expected emotional pleasure and discomfort for each of the events. Afterward, they were asked to rate their overall expected emotional pleasure and discomfort when looking at their future professional life as a whole. Results showed that expected pleasure was much larger than expected discomfort regarding both overall, peak, and average ratings. No peak-end effect was observed for overall expected discomfort which reflected the average expected discomfort across events. By contrast, overall expected pleasure was biased toward expected peak pleasure experiences. These findings indicate that student teachers judge their expected overall affect in a functional way: realistically when dealing with negative emotions but through rose-colored glasses when dealing with positive emotions.

Fluent processing leads to positive stimulus evaluations even when base rates suggest negative evaluations

Fluency is the experienced ease of ongoing mental operations, which increases the subjective positivity of stimuli attributes. This may happen because fluency is inherently positive. Alternatively, people may learn the meaning of fluency from contingencies within judgment-contexts. We test pseudocontingencies (PCs) as a mechanism through which fluency's meaning is learned. PCs are inferred correlations between two attributes due to the observation of their jointly skewed base rates - people relate what is frequent in one attribute to what is frequent in the other. Using online seller evaluations as the dependent variable, we manipulated base rates of seller name-fluency and seller reputation, creating conditions where name-fluency aligned positively or negatively with reputation. However, participants evaluated high-fluency name sellers more positively across base-rate conditions, although we observed negative PCs between seller reputation and a fluency-neutral dimension in a follow-up study. We discuss the implications for the debate regarding fluency's positive vs. malleable nature.

Typical is Trustworthy - Evidence for a Generalized Heuristic

When judging whether someone is trustworthy, people rely on the perceptual typicality of a person’s face. We tested whether a more general typical-is-trustworthy heuristic exists based on the descriptive typicality of a person. In four experiments, we provided participants with descriptive information about the typicality of target persons’ attributes (i.e., population prevalence) and measured perceived trustworthiness. Participants consistently expected descriptively typical targets to be more trustworthy than descriptively atypical targets. These findings show that typicality-based trustworthiness inferences are not only confided to perceptual typicality but also apply to descriptive typicality, suggesting a general typical-is-trustworthiness heuristic. This implies a human tendency to trust typical individuals more and, conversely, a disadvantage for atypical individuals such as minorities.

Explaining Negativity Dominance without Processing Bias

In a recent study, Shin and Niv explain both negativity and positivity biases in social evaluations as a function of the diversity and low frequency of events. We discuss why negative information is indeed more diverse and less frequent, and highlight the implications beyond social evaluations.

The Challenge of Diagnostic Inferences From Implicit Measures: The Case of Non-Evaluative Influences in the Evaluative Priming Paradigm

Implicit measures are diagnostic tools to assess attitudes and evaluations that people cannot or may not want to report. Diagnostic inferences from such tools are subject to asymmetries. We argue that (causal) conditional probabilities p(AM+|A+) of implicitly measured attitudes AM+ given the causal influence of existing attitudes A+ is typically higher than the reverse (diagnostic) conditional probability p(A+|AM+), due to non-evaluative influences on implicit measures. We substantiate this argument with evidence for non-evaluative influences on evaluative priming—specifically, similarity effects reflecting the higher similarity of positive than negative prime-target pairs; integrativity effects based on primes and targets’ potential to form meaningful semantic compounds; and congruity proportion effects that originate in individuals’ decisional strategies. We also cursorily discuss non-evaluative influences in the Implicit Association Test (IAT). These influences not only have implications for the evaluative priming paradigm in particular, but also highlight the intricacies of diagnostic inferences from implicit measures in general.

Repetition increases both the perceived truth and fakeness of information: An ecological account

People believe repeated statements more compared to new statements - they show a truth by repetition effect. In three pre-registered experiments, we show that repetition may also increase perceptions that statements are used as fake news on social media, irrespective of the factual truth or falsehood of the statements (Experiment 1 & 2), but that repetition reduces perceptions of falsehood when the context of judgment is left unspecified (Experiment 3). On a theoretical level, the findings support an ecological account of repetition effects, as opposed to either a fluency-as-positivity or to an amplification account of these effects. On a practical level, they qualify the influence of repetition on the perception of fake news.