The amplification of risk in experimental diffusion chains

Subjective Probability Increases Across Communication Chains: Introducing the Probability Escalation Effect

A severity effect has previously been documented, whereby numerical translations of verbal probability expressions are higher for severe outcomes than for non-severe outcomes. Recent work has additionally shown the same effect in the opposite direction (translating numerical probabilities into words). Here, we aimed to test whether these effects lead to an escalation of subjective probabilities across a communication chain. In four 'communication chain' studies, participants at each communication stage either translated a verbal probability expression into a number, or a number into a verbal expression (where the probability to be translated was yoked to a previous participant). Across these four studies, we found a general Probability Escalation Effect, whereby subjective probabilities increased with subsequent communications for severe, non-severe and positive events. Having ruled out some alternative explanations, we propose that the most likely explanation is in terms of communications directing attention towards an event's occurrence. Probability estimates of focal outcomes increase across communication stages.

Interdependency or submission to authority? The impacts of horizontal and vertical collectivist orientation on vaccine attitudes in mainland China

Culture has a profound impact on preventive measures during the COVID-19 pandemic. Previous research has revealed that collectivism is associated with more effective responses to COVID-19 on the national or regional level. However, the impact of different components of collectivist orientation on vaccine attitudes remains insufficiently explored on the individual level. Two survey studies conducted in August 2021 in mainland China consistently found that individual-level horizontal collectivist orientation, rather than vertical collectivist orientation, was linked with more favourable vaccine attitudes. Specifically, Study 1 (N = 731) indicated that horizontal collectivist orientation was positive associated with vaccination intention indirectly via risk perception, and horizontal collectivist orientation was also positively associated with vaccination persuasion both directly and indirectly via risk perception. Study 2 (N = 1481), employing multilevel modelling, demonstrated that the link between horizontal collectivist orientation and confidence in vaccines remained robust regardless of provincial-level variations in socioeconomic development and cultural tightness. These findings convergently suggest that the positive vaccine attitudes among mainland Chinese are primarily driven by an amplified risk perception due to concern for others, rather than submission to authority.

Curious about threats: Morbid curiosity and interest in conspiracy theories in US adults

Conspiracy theories allege secret plots between two or more powerful actors to achieve an outcome, sometimes explaining important events or proposing alternative understandings of reality in opposition to mainstream accounts, and commonly highlight the threat presented by the plot and its conspirators. Research in psychology proposes that belief in conspiracy theories is motivated by a desire to understand threats and is predicted by increased anxiety. Morbid curiosity describes the tendency to seek out information about threatening or dangerous situations and is associated with an interest in threat-related entertainment and increased anxiety. Across three studies, we investigated the relationship between morbid curiosity and conspiracy theories in US-based samples. We found that higher trait morbid curiosity was associated with higher general conspiracist beliefs (Study 1) and the perceived threat of conspiratorial explanations of events (Study 2). Using a behavioural choice paradigm, we found that participants who chose to investigate morbidly curious stimuli were more likely to choose to learn about conspiratorial explanations for events (Study 3). Greater curiosity about the minds of dangerous people was consistently the strongest predictor of conspiratorial ideation and interest. These results suggest that morbid curiosity is an important but hitherto unstudied predictor of conspiratorial interest and belief.

Humans create more novelty than ChatGPT when asked to retell a story

We compare how humans retell stories to how ChatGPT retells stories in chains of three retellings by different people or different accounts on ChatGPT. ChatGPT provides competent summaries of the original narrative texts in one step of retelling. In subsequent retellings few additional changes occur. Human retellers, by contrast, reduce the original text incrementally and by creating 55-60% of novel words and concepts (synsets) at each iteration. The retellings by both ChatGPT and humans show very stable emotion ratings, which is a puzzle for human retellers given the high degree of novel inventions across retellings. ChatGPT maintains more nouns, adjectives, and prepositions and also uses language later acquired in life, while humans use more verbs, adverbs, and negations and use language acquired at a younger age. The results reveal that spontaneous retelling by humans involves ongoing creativity, anchored by emotions, beyond the default probabilistic wording of large language models such as ChatGPT.

Resampling reduces bias amplification in experimental social networks

Large-scale social networks are thought to contribute to polarization by amplifying people's biases. However, the complexity of these technologies makes it difficult to identify the mechanisms responsible and evaluate mitigation strategies. Here we show under controlled laboratory conditions that transmission through social networks amplifies motivational biases on a simple artificial decision-making task. Participants in a large behavioural experiment showed increased rates of biased decision-making when part of a social network relative to asocial participants in 40 independently evolving populations. Drawing on ideas from Bayesian statistics, we identify a simple adjustment to content-selection algorithms that is predicted to mitigate bias amplification by generating samples of perspectives from within an individual's network that are more representative of the wider population. In two large experiments, this strategy was effective at reducing bias amplification while maintaining the benefits of information sharing. Simulations show that this algorithm can also be effective in more complex networks.

Peer-to-peer: The Social Transmission of Symptoms Online

BACKGROUND

Social learning can be highly adaptive-for example, avoiding a hotplate your friend just burnt themselves on-but it has also been implicated in symptom transmission. Social learning is particularly pertinent given the rapid increase in the use of online mediums for social interaction. Yet, little is known about the social transmission of symptoms online or social chains extending further than a single model-observer interaction.

PURPOSE

To explore whether socially induced symptoms could be propagated through a three-generation social transmission chain in an online setting.

METHODS

We explored the social transmission of cybersickness following a virtual reality (VR) experience through online webcam interactions. One hundred and seventy-seven adults viewed a VR video in one of four links along a social transmission chain, after: viewing an actor model cybersickness to the VR video (First-Generation); viewing the First-Generation participant undergo VR (Second-Generation); viewing the Second-Generation participant undergo VR (Third-Generation); or naïve (Control).

RESULTS

Cybersickness was strongest in First-Generation participants, indicating social transmission from the model. This was mediated by expectancy and anxiety. Whether or not subsequent generations experienced cybersickness depended on what the observed participant verbally reported, which is consistent with social transmission.

CONCLUSIONS

Results demonstrate that symptoms can be readily transmitted online, and that expectancy and anxiety are involved. Although it is inconclusive as to whether symptoms can propagate along a social transmission chain, there is some evidence of protection from symptoms when a model who does not report any symptoms is observed. As such, this research highlights the role of social transmission in the modulation of symptoms through virtual mediums.

The role of position in consensus dynamics of polarizable networks

Communication constraints often complicate group decision-making. In this experiment, we investigate how the network position of opinionated group members determines both the speed and the outcome of group consensus in 7-member communication networks susceptible to polarization. To this end, we implemented an online version of a color coordination task within experimentally controlled communication networks. In 72 networks, one individual was incentivized to prefer one of two options. In 156 networks, two individuals were incentivized to prefer conflicting options. The network positions of incentivized individuals were varied. In networks with a single incentivized individual, network position played no significant role in either the speed or outcome of consensus decisions. For conflicts, the incentivized individual with more neighbors was more likely to sway the group to their preferred outcome. Furthermore, consensus emerged more slowly when the opponents had the same number of neighbors, but could not see each other's votes directly. These results suggest that the visibility of an opinion is key to wielding group influence, and that specific structures are sufficient to run communication networks into polarization, hindering a speedy consensus.

Quantifying the retention of emotions across story retellings

Story retelling is a fundamental medium for the transmission of information between individuals and among social groups. Besides conveying factual information, stories also contain affective information. Though natural language processing techniques have advanced considerably in recent years, the extent to which machines can be trained to identify and track emotions across retellings is unknown. This study leverages the powerful RoBERTa model, based on a transformer architecture, to derive emotion-rich story embeddings from a unique dataset of 25,728 story retellings. The initial stories were centered around five emotional events (joy, sadness, embarrassment, risk, and disgust-though the stories did not contain these emotion words) and three intensities (high, medium, and low). Our results indicate (1) that RoBERTa can identify emotions in stories it was not trained on, (2) that the five emotions and their intensities are preserved when they are transmitted in the form of retellings, (3) that the emotions in stories are increasingly well-preserved as they experience additional retellings, and (4) that among the five emotions, risk and disgust are least well-preserved, compared with joy, sadness, and embarrassment. This work is a first step toward quantifying situation-driven emotions with machines.

Social Media Overload and Anxiety Among University Students During the COVID-19 Omicron Wave Lockdown: A Cross-Sectional Study in Shanghai, China, 2022

Objectives: The increase in the intensity of social media use during the COVID-19 lockdown has affected mental health. Therefore, it is of practical implications to explore the association between social media overload and anxiety and the underlying mechanisms. Methods: Using data from 644 university students during the COVID-19 blockade in Shanghai from March to April 2022, the chain mediation model of information strain and risk perception of omicron between social media overload and anxiety was then tested using the macro PROCESS4.0 tool. Results: The findings showed that social media overload (including information overload and social overload) was positively associated with anxiety. This relationship was mediated by information strain and risk perception of Omicron. A chain mediating role of information strain and risk perception of Omicron has also been proved in this study. Conclusion: Social media overload has a positive effect on anxiety by increasing information strain and risk perception of Omicron. This study provides some implications for future interventions on how to use social media properly for mental health during the pandemic and health management of urban governance.

Political conspiracy theories as tools for mobilization and signaling

Political conspiracist communities emerge and bind around hard-to-falsify narratives about political opponents or elites convening to secretly exploit the public in contexts of perceived political conflict. While the narratives appear descriptive, we propose that their content as well as the cognitive systems regulating their endorsement and dissemination may have co-evolved, at least in part, to reach coalitional goals: To drive allies' attention to the social threat to increase their commitment and coordination for collective action, and to signal devotion to gain within-group status. Those evolutionary social functions may be best fulfilled if individuals endorse the conspiratorial narrative sincerely.

The social amplification of risk framework: New perspectives

Several decades have elapsed since the introduction in 1988 of the social amplification of risk framework (SARF) by researchers from Clark University and Decision Research. SARF was offered as an umbrella under which social, psychological, and cultural theories of risk could be integrated and thereby supplement technical risk analyses. Some critics suggest that SARF cannot be tested thus, the framework is useful, at most, as a post hoc analysis of some kinds of risks. Others counter that predictability is not required for a framework to be useful and that SARF is an effective tool in organizing data related to public perceptions, values, and behaviors. It can also be used to design more effective risk communication and public engagement strategies. SARF also suggests how to conceptually view the dynamics of social media channels, despite the fact that SARF was developed before the explosion of global digital platforms. The papers in this special issue consider developments, refinements, critiques, contributions, extensions of the approach to new risk issues, as well as the findings and hypotheses that have grown out of what is now close to three decades of empirical research. This introductory paper provides background on SARF, presents a literature review since 2003, introduces the contributions to this issue, and highlights several areas for future research.

Social amplification of risks and the clean energy transformation: Elaborating on the four attributes of information

The social amplification of risk framework (SARF) was developed to help comprehend how emerging contributions about the psychological, social, and cultural dimensions of risk could work in unison to impact decision making about risk. The framework proposed that risks are amplified or attenuated by interested parties employing different rhetorical strategies to give information about risk a certain "spin." The original literature identified four "attributes of information." However, despite the longevity of the framework, these have not been explicated in detail. Here we add depth and clarity by examining how amplification stations send risk signals that amplify or attenuate risk by emphasizing these different attributes of information. Drawing on a wealth of qualitative data from two case studies of offshore wind turbine siting off the coasts of Maryland and Delaware and guided by an extensive literature review, we reveal the strategies interested parties are using to influence siting decisions and risk management. The paper explores the usefulness of SARF in organizing qualitative information and sharpening insights on participatory risk governance and the nuances of public responses to a relatively new low-carbon technology. The authors conclude that the framework is valuable for analyzing stakeholder information while also recognizing limitations that may be addressed with some targeted future research.

Conformist social learning leads to self-organised prevention against adverse bias in risky decision making

Given the ubiquity of potentially adverse behavioural bias owing to myopic trial-and-error learning, it seems paradoxical that improvements in decision-making performance through conformist social learning, a process widely considered to be bias amplification, still prevail in animal collective behaviour. Here we show, through model analyses and large-scale interactive behavioural experiments with 585 human subjects, that conformist influence can indeed promote favourable risk taking in repeated experience-based decision making, even though many individuals are systematically biased towards adverse risk aversion. Although strong positive feedback conferred by copying the majority's behaviour could result in unfavourable informational cascades, our differential equation model of collective behavioural dynamics identified a key role for increasing exploration by negative feedback arising when a weak minority influence undermines the inherent behavioural bias. This 'collective behavioural rescue', emerging through coordination of positive and negative feedback, highlights a benefit of collective learning in a broader range of environmental conditions than previously assumed and resolves the ostensible paradox of adaptive collective behavioural flexibility under conformist influences.

Individual and collective learning in groups facing danger

While social networks jeopardize people’s well-being by working as diffusion pathways of falsehood, they may also help people overcome the challenge of misinformation with time and experience. Here I examine how social networks provide learning facilitation using an experiment involving an iterated decision-making game simulating an unpredictable situation faced by a group (2786 subjects in 120 groups). This study shows that, while social networks initially spread false information and suppress necessary actions, with tie rewiring, on the other hand, they facilitate improvement in people's decision-making across time. It also shows that the network's learning facilitation results from the integration of individual experiences into structural changes. In sum, social networks can support collective learning when they are built through people's experiences and accumulated relationships.

Serial reproduction of narratives preserves emotional appraisals

We conducted the largest multiple-iteration retelling study to date (12,840 participants and 19,086 retellings) with two different studies that test how emotional appraisals are transmitted across retellings. We use a novel Bayesian model that tracks changes across retellings. Study 1 examines the preservation of appraisals of happy and sad stories and finds that retellings preserve the story's degree of happiness and sadness even when length shrinks and aspects of story coherence and rationalisation deteriorate. Study 2 compared the transmission of appraisals of happiness and sadness with embarrassment, disgust, and risk. Appraisals of happiness, sadness, and also embarrassment showed high appraisal preservation, while disgust and risk were not well preserved. We conclude that participants in our studies encoded happy and sad stories by encapsulating the events and details into an overall emotional appraisal of the story and that this processing strategy might also apply to stories involving other emotions like embarrassment. The emotional appraisal played a key role in retelling by helping to guide the selection, invention, and ordering of the story elements. Hence, we posit that emotion appraisals can operate as anchors for remembering and retelling stories, thus playing an important role in narrative communication.

Psychological Drivers of Individual Differences in Risk Perception: A Systematic Case Study Focusing on 5G

What drives people's perceptions of novel risks, and how malleable are such risk perceptions? Psychological research has identified multiple potential drivers of risk perception, but no studies have yet tested within a unified analytic framework how well each of these drivers accounts for individual differences in large population samples. To provide such a framework, I harnessed the deployment of 5G-the latest generation of cellular network technology. Specifically, I conducted a multiverse analysis using a representative population sample in Switzerland (Study 1; N = 2,919 individuals between 15 and 94 years old), finding that interindividual differences in risk perceptions were strongly associated with hazard-related drivers (e.g., trust in the institutions regulating 5G, dread) and person-specific drivers (e.g., electromagnetic hypersensitivity)-and strongly predictive of people's policy-related attitudes (e.g., voting intentions). Further, a field experiment based on a national expert report on 5G (N = 839 individuals in a longitudinal sample between 17 and 79 years old) identified links between intraindividual changes in psychological drivers and perceived risk, thus highlighting potential targets for future policy interventions.

Socially Situated Transmission: The Bias to Transmit Negative Information is Moderated by the Social Context

Cultural evolutionary theory has identified a range of cognitive biases that guide human social learning. Naturalistic and experimental studies indicate transmission biases favoring negative and positive information. To address these conflicting findings, the present study takes a socially situated view of information transmission, which predicts that bias expression will depend on the social context. We report a large-scale experiment (N = 425) that manipulated the social context and examined its effect on the transmission of the positive and negative information contained in a narrative text. In each social context, information was progressively lost as it was transmitted from person to person, but negative information survived better than positive information, supporting a negative transmission bias. Importantly, the negative transmission bias was moderated by the social context: Higher social connectivity weakened the bias to transmit negative information, supporting a socially situated account of information transmission. Our findings indicate that our evolved cognitive preferences can be moderated by our social goals.

Is the Mind a Network? Maps, Vehicles, and Skyhooks in Cognitive Network Science

Cognitive researchers often carve cognition up into structures and processes. Cognitive processes operate on structures, like vehicles driving over a map. Language alongside semantic and episodic memory are proposed to have structure, as are perceptual systems. Over these structures, processes operate to construct memory and solve problems by retrieving and manipulating information. Network science offers an approach to representing cognitive structures and has made tremendous inroads into understanding the nature of cognitive structure and process. But is the mind a network? If so, what kind? In this article, we briefly review the main metaphors, assumptions, and pitfalls prevalent in cognitive network science (maps and vehicles; one network/process to rule them all), highlight the need for new metaphors that elaborate on the map-and-vehicle framework (wormholes, skyhooks, and generators), and present open questions in studying the mind as a network (the challenge of capturing network change, what should the edges of cognitive networks be made of, and aggregated vs. individual-based networks). One critical lesson of this exercise is that the richness of the mind as network approach makes it a powerful tool in its own right; it has helped to make our assumptions more visible, generating new and fascinating questions, and enriching the prospects for future research. A second lesson is that the mind as a network-though useful-is incomplete. The mind is not a network, but it may contain them.

Access to Vaccination Information and Confidence/Hesitancy Towards Childhood Vaccination: A Cross-Sectional Survey in China

Access to vaccination information could influence public attitudes towards vaccination. This study investigated the number and types of vaccination-related information sources, and estimated their associations with vaccine confidence and hesitancy in China. In January 2019, we conducted a cross-sectional survey in China, and 2122 caregivers with children <6 years completed self-administered questionnaires. Logistic regressions were used to assess associations between caregivers’ primary information sources and vaccine confidence/hesitancy. A majority (72%) of caregivers had multiple sources of vaccination-related information. The proportions of caregivers reporting professional sources, media, and peers as primary information sources were 81%, 63%, and 26%. Internal migrants were less likely to get information from professional sources; more educated and wealthier caregivers reported more information sources and were more likely to get information from media and peers. Caregivers who reported professional information sources had significantly higher odds of being confident about the safety of vaccines and lower odds of being hesitant toward vaccination than those who did not. Caregivers who reported the media as a primary information source had significantly higher odds of being hesitant toward vaccination than those who did not. To address vaccine hesitancy, it is essential to promote universal access to professional vaccination-related information sources, and to use the media to disseminate evidence-based information and clarify misinformation. Health communication should target internal migrants, and more educated and wealthier caregivers.

Similarity in functional brain connectivity at rest predicts interpersonal closeness in the social network of an entire village

People often have the intuition that they are similar to their friends, yet evidence for homophily (being friends with similar others) based on self-reported personality is inconsistent. Functional connectomes-patterns of spontaneous synchronization across the brain-are stable within individuals and predict how people tend to think and behave. Thus, they may capture interindividual variability in latent traits that are particularly similar among friends but that might elude self-report. Here, we examined interpersonal similarity in functional connectivity at rest-that is, in the absence of external stimuli-and tested if functional connectome similarity is associated with proximity in a real-world social network. The social network of a remote village was reconstructed; a subset of residents underwent functional magnetic resonance imaging. Similarity in functional connectomes was positively related to social network proximity, particularly in the default mode network. Controlling for similarities in demographic and personality data (the Big Five personality traits) yielded similar results. Thus, functional connectomes may capture latent interpersonal similarities between friends that are not fully captured by commonly used demographic or personality measures. The localization of these results suggests how friends may be particularly similar to one another. Additionally, geographic proximity moderated the relationship between neural similarity and social network proximity, suggesting that such associations are particularly strong among people who live particularly close to one another. These findings suggest that social connectivity is reflected in signatures of brain functional connectivity, consistent with the common intuition that friends share similarities that go beyond, for example, demographic similarities.

A brief history of risk

Despite increasing life expectancy and high levels of welfare, health care, and public safety in most post-industrial countries, the public discourse often revolves around perceived threats. Terrorism, global pandemics, and environmental catastrophes are just a few of the risks that dominate media coverage. Is this public discourse on risk disconnected from reality? To examine this issue, we analyzed the dynamics of the risk discourse in two natural language text corpora. Specifically, we tracked latent semantic patterns over a period of 150 years to address four questions: First, we examined how the frequency of the word risk has changed over historical time. Is the construct of risk playing an ever-increasing role in the public discourse, as the sociological notion of a 'risk society' suggests? Second, we investigated how the sentiments for the words co-occurring with risk have changed. Are the connotations of risk becoming increasingly ominous? Third, how has the meaning of risk changed relative to close associates such as danger and hazard? Is risk more subject to semantic change? Finally, we decompose the construct of risk into the specific topics with which it has been associated and track those topics over historical time. This brief history of the semantics of risk reveals new and surprising insights-a fourfold increase in frequency, increasingly negative sentiment, a semantic drift toward forecasting and prevention, and a shift away from war toward chronic disease-reflecting the conceptual evolution of risk in the archeological records of public discourse.

Reviews on common objectives and evaluation indicators for risk communication activities from 2011 to 2017

BACKGROUND

Risk communication is widely accepted as a significant factor for policy makers, academic researchers, and practitioners in diverse fields. However, there remains a lack of comprehensive knowledge about how risk communication is currently conducted across fields and about the way risk communication is evaluated.

METHODOLOGY

This study systematically searched for materials from three scholarly search engines and one journal with a single search term of "risk communication." The eligibility assessment selected peer-reviewed articles published in English that evaluated risk communication activities. Emphasis was placed on articles published in recent years accounting for about half of the pre-selected ones. Data on field of study, intervention timing, target audience, communication type, and objectives/evaluation indicators was extracted from the articles. Patterns of objectives/evaluation indicators used in risk communication activities were compared with those of the definitions and purposes of risk communication stated by relevant organizations. Association analysis was conducted based on study fields and objectives/evaluation indicators.

RESULTS

The screening process yielded 292 articles that were published between 2011 and 2017 in various fields, such as medicine, food safety, chemical substances, and disasters/emergencies. The review process showed that many activities were performed in the medical field, during non-/pre-crisis periods. Recent activities primarily targeted citizens/Non-Profit Organizations (NPOs), and was disseminated in the form of large group or mass communication. While "knowledge increase," "change in risk perception and concern alleviation," and "decision making and behavior change" were commonly addressed in practice, "trust-building" and "reduction in psychological distress" were rarely focused. The analysis also indicated that the medical field tends to perform risk communication at the individual or small group level, in contrast to the food safety field. Further, risk communications in the non-/pre-crisis period are more likely to aim at "changes in risk perception and concern alleviation" than those in the crisis period. Risk communications that aim at "changes in risk perception and concern alleviation" are likely to be presented in a large group or mass communication, whereas those that aim at "decision making and behavior change" are likely to be conducted at the individual or small group level.

CONCLUSION

An overview of recent activities may provide those who engage in risk communication with an opportunity to learn from practices in different fields or those conducted in different intervention timings. Devoting greater attention to trust building and reduction in psychological distress and exploring non-citizen/NPO stakeholders' needs would be beneficial across academic and professional disciplines.

Acute Stress Reduces the Social Amplification of Risk Perception

Risk perceptions typically underlie a complex social dynamic: Risk-related information is transmitted between individuals, this information influences risk perceptions, and risk perceptions influence which information is transmitted. This can lead to a social amplification of risk. We test how stress, a widespread affective state, influences the social dynamics of risk perception. Participants (N = 146) read articles about the controversial antibacterial agent Triclosan and were then asked to inform another person about Triclosan. Before and after reading the articles, participants reported their concern about Triclosan. Stress exposure before the task led to a smaller increase in concern in response to the articles. The stronger the increase in cortisol, the smaller the increase in concern. Furthermore, participants in the stress group transmitted less negative information about Triclosan to others. In contrast, participants’ subjective feelings of stress were associated with higher concern and more alarming risk communication. We conclude that feeling stressed can amplify risk perception, whereas the endocrine stress reaction can attenuate risk perception when information about risk is exchanged in a social context.

Collective communication and behaviour in response to uncertain 'Danger' in network experiments

In emergencies, social coordination is especially challenging. People connected with each other may respond better or worse to an uncertain danger than isolated individuals. We performed experiments involving a novel scenario simulating an unpredictable situation faced by a group in which 2480 subjects in 108 groups had to both communicate information and decide whether to ‘evacuate’. We manipulated the permissible sorts of interpersonal communication and varied group topology and size. Compared to groups of isolated individuals, we find that communication networks suppress necessary evacuations because of the spontaneous and diffuse emergence of false reassurance; yet, communication networks also restrain unnecessary evacuations in situations without disasters. At the individual level, subjects have thresholds for responding to social information that are sensitive to the negativity, but not the actual accuracy, of the signals being transmitted. Social networks can function poorly as pathways for inconvenient truths that people would rather ignore.

Understanding risk communication for prevention and control of vector-borne diseases: A mixed-method study in Curaçao

Background

Risk communication (RC) is an essential tool for the prevention and control of diseases as it impacts risk perception, increases awareness and might change behaviour. It is the interactive exchange of information about risks among experts and people. Effective RC can minimize the impact that diseases such as dengue, chikungunya and Zika have on populations. This study aimed to understand RC regarding vector-borne diseases in its social context and from the viewpoint of the audience to strengthen RC strategies in Curaçao.

Methods

In 2015, a cross-sectional mixed-method study applying focus group discussions (n = 7), in-depth interviews (n = 20) and a structured survey questionnaire (n = 339) was done in Curaçao. The study was designed based on the Health Belief Model and the Theory of Planned Behaviour. In addition, the Social Amplification of Risk Framework and the theory of cultural schemas were applied to understand RC in the social context.

Results

Television, radio and newspapers were the most important channels of information regarding dengue and chikungunya. Moreover, individuals also reported receiving information via social media, the internet and family/friends. Interestingly, the use of internet to obtain information diminished with age, while females were more likely to use internet compared to men. These key findings were statistically significant. An important outcome was that the risk perception towards chikungunya at the beginning of the outbreak was attenuated. This might be due to the (perceived) lack of RC before the epidemic. This same risk perception was amplified later during the outbreak by the increased exposure to information. Lastly, we show how cultural schemas influence people’s perception regarding preventive measures and treatment of chikungunya and dengue.

Conclusions

Data obtained emphasise the importance of understanding the user of media platforms and sharing information in a timely fashion through a transparent process with the content that convinces people of the seriousness of the matter.

Vector-borne diseases (VBDs) such as dengue, chikungunya and Zika are an increasing public health concern worldwide. The mentioned VBDs are transmitted to humans through the bite of an infected mosquito from the Aedes species. Preventing or reducing VBDs continues to depend mainly on vector control and interrupting human-vector contact. Risk communication (RC) is the interactive exchange of information about hazards among experts and individuals. As it influences individuals’ behaviour, a better understanding of how it works is vital to improving RC strategies in the context of VBD prevention and control strategies. Our study highlighted the complexity of this matter as we found that there are multiple factors, including the volume of information, trust, experience with a similar disease and cultural schemas that determine how people cope with risk and information. We recommend broadening the use and scope of media platforms to share information and to customise the messages taking the cultural schemas of the community into account.

The cognitive foundations of misinformation on science: What we know and what scientists can do about it

Mis information and misunderstanding of science can partially explained by cognitive processes rooted in our evolutionary past. Science communication can use this knowledge to overcome these cognitive limits.

Risk Evaluation of “Not-In-My-Back-Yard” Conflict Potential in Facilities Group: A Case Study of Chemical Park in Xuwei New District, China

The social risk of chemical industry park projects attracts much attention, as they are perceived to yield strong environmental risks. This paper systematically evaluates the social risk of Xuwei Chemical Park in China, which was investigated as an example to guide the risk control strategy of conflict in industrial facilities for developing countries. The results show that residents and government departments have a resistance to the risks of the project as a stronger sense of group risk perception (the value is 7 × 10−6) compared with the basic value of 7 × 10−5. By contrast, the low value of group risk perception was evaluated in an enterprise group (7 × 10−4), indicating that the risks of petrochemical projects are often accepted. The expert group’s risk perception regarding petrochemical projects is consistent with the basic value. This is a very interesting finding indicating that the greater the experience, the more the support for petrochemical projects. The knowledge and information from education or experience improve the judgment of the risk of the facility, which increases the individual’s rational assessment comprehension of risk. Moreover, factors that are significantly related to residents’ attitudes are information cognitive factors (trust in information publicity and petrochemical project understanding), and project influencing factors (project planning rationality, quality of life improvement, and economic development satisfaction). Among them, the degree of trust in information disclosure has the highest degree of influence, followed by the level of education, while the satisfaction with economic development has the lowest degree of influence. Therefore, improving the trust of residents in the information disclosure of petrochemical projects should be the core of the government’s risk control policy.

Comparing Groups of Independent Solvers and Transmission Chains as Methods for Collective Problem-Solving

Groups can be very successful problem-solvers. This collective achievement crucially depends on how the group is structured, that is, how information flows between members and how individual contributions are merged. Numerous methods have been proposed, which can be divided into two major categories: those that involve an exchange of information between the group members, and those that do not. Here we compare two instances of such methods for solving multi-dimensional problems: (1) transmission chains, where individuals tackle the problem one after the other, each one building on the solution of the predecessor and (2) groups of independent solvers, where individuals tackle the problem independently, and the best solution found in the group is selected afterwards. By means of numerical simulations and experimental observations, we show that the best performing method is determined by the interplay between two key factors: the individual's degrees of freedom as an aspect of skill and the complexity of the problem. We find that transmission chains are superior either when the problem is rather smooth, or when the group is composed of rather unskilled individuals with a low degree of freedom. On the contrary, groups of independent solvers are preferable for rugged problems or for groups of rather skillful individuals with a high degree of freedom. Finally, we deepen the comparison by studying the impact of the group size and diversity. Our research stresses that efficient collective problem-solving requires a good matching between the nature of the problem and the structure of the group.

The echo in flu-vaccination echo chambers: Selective attention trumps social influence

BACKGROUND

Online discussions may impact the willingness to get vaccinated. This experiment tests how groups of individuals with consistent and inconsistent attitudes towards flu vaccination attend to and convey information online, and how they alter their corresponding risk perceptions.

METHODS

Out of 1859 MTurkers, we pre-selected 208 people with negative and 221 people with positive attitudes towards flu vaccinations into homogeneous or heterogeneous 3-link experimental diffusion chains. We assessed (i) which information about flu vaccinations participants conveyed to the subsequent link, (ii) how flu-vaccination related perceptions were altered by incoming messages, and (iii) how participants perceived incoming information.

RESULTS

Participants (i) selectively conveyed attitude-consistent information, but exhibited no overall anti-vaccination bias, (ii) were reluctant to alter their flu-vaccination related perceptions in response to messages, and (iii) evaluated incoming information consistent with their prior attitudes as more convincing.

DISCUSSION

Flu-vaccination related perceptions are resilient against contradictions and bias online communication. Contrary to expectations, there was no sign of amplification of anti-vaccine attitudes by online communication.

Fact vs. Affect in the Telephone Game: All Levels of Surprise Are Retold With High Accuracy, Even Independently of Facts

When people retell stories, what guides their retelling? Most previous research on story retelling and story comprehension has focused on information accuracy as the key measure of stability in transmission. This paper suggests that there is a second, affective, dimension that provides stability for retellings, namely the audience affect of surprise. In a large-sample study with multiple iterations of retellings, we found evidence that people are quite accurate in preserving all degrees of surprisingness in serial reproduction – even when the event that produced the surprisingness in the original story is dropped or changed. Thus, we propose that the preservation of affect is an implicit goal of retelling: merely do retellers not recall highly surprising events better, but rather they register all levels of surprisingness precisely and aim to surprise their implied audience to same degree. This study used 2,389 participants.

Significance Statement: Story retelling is a process whereby cultural information is transmitted horizontally across social networks and vertically down generations. For the most part, retelling research has focused on the relevance and stability of factual information, “who did what, where, when, and why”; comparatively little is known about the transmission of affective information. We suggest that affect can serve as a second axis of stability for retelling, partially independent from factual information. In serial reproduction tasks modeled after the telephone game, we find that surprisingness of stories is well preserved across retellings – even when the facts and events of the story are not. The findings are significant for the communication of information, and thereby also the stability and transformation of culture in general.

Rethinking Social Amplification of Risk: Social Media and Zika in Three Languages

Using the Zika outbreak as a context of inquiry, this study examines how assigning blame on social media relates to the social amplification of risk framework (SARF). Past research has discussed the relationship between the SARF and traditional mass media, but the role of social media platforms in amplification or attenuation of risk perceptions remains understudied. Moreover, the communication and perceptions of Zika-related risk are not limited to discussions in English. To capture conversations in languages spoken by affected countries, this study combines data in English, Spanish, and Portuguese. To better understand the assignment of blame and perceptions of risk in new media environments, we looked at three different facets of conversations surrounding Zika on Facebook and Twitter: the prominence of blame in each language, how specific groups were discussed throughout the Zika outbreak, and the sentiment expressed about genetically engineered (GE) mosquitoes. We combined machine learning with human coding to analyze public discourse in all three languages. We found differences between languages and platforms in the amount of blame assigned to different groups. We also found more negative sentiments expressed about GE mosquitoes on Facebook than on Twitter. These meaningful differences only emerge from analyses across the three different languages and platforms, pointing to the importance of multilingual approaches for risk communication research. Specific recommendations for outbreak and risk communication practitioners are also discussed.

The Dark Side of Information Proliferation

There are well-understood psychological limits on our capacity to process information. As information proliferation-the consumption and sharing of information-increases through social media and other communications technology, these limits create an attentional bottleneck, favoring information that is more likely to be searched for, attended to, comprehended, encoded, and later reproduced. In information-rich environments, this bottleneck influences the evolution of information via four forces of cognitive selection, selecting for information that is belief-consistent, negative, social, and predictive. Selection for belief-consistent information leads balanced information to support increasingly polarized views. Selection for negative information amplifies information about downside risks and crowds out potential benefits. Selection for social information drives herding, impairs objective assessments, and reduces exploration for solutions to hard problems. Selection for predictive patterns drives overfitting, the replication crisis, and risk seeking. This article summarizes the negative implications of these forces of cognitive selection and presents eight warnings that represent severe pitfalls for the naive "informavore," accelerating extremism, hysteria, herding, and the proliferation of misinformation.

Bad News Has Wings: Dread Risk Mediates Social Amplification in Risk Communication

Social diffusion of information amplifies risk through processes of birth, death, and distortion of message content. Dread risk-involving uncontrollable, fatal, involuntary, and catastrophic outcomes (e.g., terrorist attacks and nuclear accidents)-may be particularly susceptible to amplification because of the psychological biases inherent in dread risk avoidance. To test this, initially balanced information about high or low dread topics was given to a set of individuals who then communicated this information through diffusion chains, each person passing a message to the next. A subset of these chains were also reexposed to the original information. We measured prior knowledge, perceived risk before and after transmission, and, at each link, number of positive and negative statements. Results showed that the more a message was transmitted the more negative statements it contained. This was highest for the high dread topic. Increased perceived risk and production of negative messages was closely related to the amount of negative information that was received, with domain knowledge mitigating this effect. Reexposure to the initial information was ineffectual in reducing bias, demonstrating the enhanced danger of socially transmitted information.

Virtual Sensing and Virtual Reality: How New Technologies Can Boost Research on Crowd Dynamics

The collective behavior of human crowds often exhibits surprisingly regular patterns of movement. These patterns stem from social interactions between pedestrians such as when individuals imitate others, follow their neighbors, avoid collisions with other pedestrians, or push each other. While some of these patterns are beneficial and promote efficient collective motion, others can seriously disrupt the flow, ultimately leading to deadly crowd disasters. Understanding the dynamics of crowd movements can help urban planners manage crowd safety in dense urban areas and develop an understanding of dynamic social systems. However, the study of crowd behavior has been hindered by technical and methodological challenges. Laboratory experiments involving large crowds can be difficult to organize, and quantitative field data collected from surveillance cameras are difficult to evaluate. Nevertheless, crowd research has undergone important developments in the past few years that have led to numerous research opportunities. For example, the development of crowd monitoring based on the virtual signals emitted by pedestrians' smartphones has changed the way researchers collect and analyze live field data. In addition, the use of virtual reality, and multi-user platforms in particular, have paved the way for new types of experiments. In this review, we describe these methodological developments in detail and discuss how these novel technologies can be used to deepen our understanding of crowd behavior.

Factors influencing residents' acceptance (support) of remediation technologies

An increasing diversity of technologies are being used to remediate contaminated sites, yet there remains little understanding of the level of acceptance that residents living near these sites hold for these technologies, and what factors influence their level of acceptance. This lack of understanding hinders the remediation industry's ability to effectively engage with these residents about remediation technology selection, at a time when such engagement is become part and parcel of remediation policy and practice. The study develops on wider research into public acceptance of technologies, using data from a telephone survey of 2009 residents living near thirteen contaminated sites across Australia. Within the survey acceptance is measured through residents' level of support for the application of remediation technologies in their local area. Firstly, a regression analysis of closed-ended questions, and coding of open-ended questions are combined to identify the main predictors of residents' support for remediation technologies. Secondly, coding of open-ended questions was analysed using Crawford and Ostrom's Institutional Grammar Tool to identify norms and sanctions guiding residents' willingness to negotiate their support. The research identifies factors associated with the residents' personal and demographic characteristics, their physical context and engagement with institution during remediation processes, and the technologies themselves which predict residents' level of support for the application of remediation technologies. Bioremediation technologies had higher levels of support than chemical, thermal and physical technologies. Furthermore, the paper identifies a core set of norms and sanctions residents use to negotiate their level of support for remediation technologies.

The primary case is not enough: Variation among individuals, groups and social networks modify bacterial transmission dynamics

The traits of the primary case of an infectious disease outbreak, and the circumstances for their aetiology, potentially influence the trajectory of transmission dynamics. However, these dynamics likely also depend on the traits of the individuals with whom the primary case interacts. We used the social spider Stegodyphus dumicola to test how the traits of the primary case, group phenotypic composition and group size interact to facilitate the transmission of a GFP-labelled cuticular bacterium. We also compared bacterial transmission across experimentally generated "daisy-chain" vs. "star" networks of social interactions. Finally, we compared social network structure across groups of different sizes. Groups of 10 spiders experienced more bacterial transmission events compared to groups of 30 spiders, regardless of groups' behavioural composition. Groups containing only one bold spider experienced the lowest levels of bacterial transmission regardless of group size. We found no evidence for the traits of the primary case influencing any transmission dynamics. In a second experiment, bacteria were transmitted to more individuals in experimentally induced star networks than in daisy-chains, on which transmission never exceeded three steps. In both experimental network types, transmission success depended jointly on the behavioural traits of the interacting individuals; however, the behavioural traits of the primary case were only important for transmission on star networks. Larger social groups exhibited lower interaction density (i.e. had a low ratio of observed to possible connections) and were more modular, i.e. they had more connections between nodes within a subgroup and fewer connections across subgroups. Thus, larger groups may restrict transmission by forming fewer interactions and by isolating subgroups that interacted with the primary case. These findings suggest that accounting for the traits of single exposed hosts has less power in predicting transmission dynamics compared to the larger scale factors of the social groups in which they reside. Factors like group size and phenotypic composition appear to alter social interaction patterns, which leads to differential transmission of microbes.

Dynamical networks of influence in small group discussions

In many domains of life, business and management, numerous problems are addressed by small groups of individuals engaged in face-to-face discussions. While research in social psychology has a long history of studying the determinants of small group performances, the internal dynamics that govern a group discussion are not yet well understood. Here, we rely on computational methods based on network analyses and opinion dynamics to describe how individuals influence each other during a group discussion. We consider the situation in which a small group of three individuals engages in a discussion to solve an estimation task. We propose a model describing how group members gradually influence each other and revise their judgments over the course of the discussion. The main component of the model is an influence network-a weighted, directed graph that determines the extent to which individuals influence each other during the discussion. In simulations, we first study the optimal structure of the influence network that yields the best group performances. Then, we implement a social learning process by which individuals adapt to the past performance of their peers, thereby affecting the structure of the influence network in the long run. We explore the mechanisms underlying the emergence of efficient or maladaptive networks and show that the influence network can converge towards the optimal one, but only when individuals exhibit a social discounting bias by downgrading the relative performances of their peers. Finally, we find a late-speaker effect, whereby individuals who speak later in the discussion are perceived more positively in the long run and are thus more influential. The numerous predictions of the model can serve as a basis for future experiments, and this work opens research on small group discussion to computational social sciences.

Risk Perception and Risk Talk: The Case of the Fukushima Daiichi Nuclear Radiation Risk

Individuals' perceptions and their interpersonal communication about a risk event, or risk talk, can play a significant role in the formation of societal responses to the risk event. As they formulate their risk opinions and speak to others, risk information can circulate through their social networks and contribute to the construction of their risk information environment. In the present study, Japanese citizens' risk perception and risk talk were examined in the context of the Fukushima Daiichi nuclear radiation risk. We hypothesized and found that the risk information environment and risk literacy (i.e., competencies to understand and use risk information) interact to influence their risk perception and risk talk. In particular, risk literacy tends to stabilize people's risk perceptions and their risk communications. Nevertheless, there were some subtle differences between risk perception and communication, suggesting the importance of further examination of interpersonal risk communication and its role in the societal responses to risk events.

Engaging with residents' perceived risks and benefits about technologies as a way of resolving remediation dilemmas

In recent decades the diversity of remediation technologies has increased significantly, with the breadth of technologies ranging from dig and dump to emergent technologies like phytoremediation and nanoremediation. The benefits of these technologies to the environment and human health are believed to be substantial. However, they also potentially constitute risks. Whilst there is a growing body of knowledge about the risks and benefits of these technologies from the perspective of experts, little is known about how residents perceive the risks and benefits of the application of these technologies to address contaminants in their local environment. This absence of knowledge poses a challenge to remediation practitioners and policy makers who are increasingly seeking to engage these affected local residents in choosing technology applications. Building on broader research into the perceived benefits and risks of technologies, and data from a telephone survey of 2009 residents living near 13 contaminated sites in Australia, regression analysis of closed-ended survey questions and coding of open-ended questions are combined to identify the main predictors of resident's perceived levels of risk and benefit to resident's health and to their local environment from remediation technologies. This research identifies a range of factors associated with the residents' physical context, their engagement with institutions during remediation processes, and the technologies which are associated with residents' level of perceived risk and benefit for human health and the local environment. The analysis found that bioremediation technologies were perceived as less risky and more beneficial than chemical, thermal and physical technologies. The paper also supports broader technology research that reports an inverse correlation between levels of perceived risks and benefits. In addition, the paper reveals the types of risks and benefits to human health and the local environment that residents most commonly associate with remediation technologies.

Reach and speed of judgment propagation in the laboratory

In recent years, a large body of research has demonstrated that judgments and behaviors can propagate from person to person. Phenomena as diverse as political mobilization, health practices, altruism, and emotional states exhibit similar dynamics of social contagion. The precise mechanisms of judgment propagation are not well understood, however, because it is difficult to control for confounding factors such as homophily or dynamic network structures. We introduce an experimental design that renders possible the stringent study of judgment propagation. In this design, experimental chains of individuals can revise their initial judgment in a visual perception task after observing a predecessor's judgment. The positioning of a very good performer at the top of a chain created a performance gap, which triggered waves of judgment propagation down the chain. We evaluated the dynamics of judgment propagation experimentally. Despite strong social influence within pairs of individuals, the reach of judgment propagation across a chain rarely exceeded a social distance of three to four degrees of separation. Furthermore, computer simulations showed that the speed of judgment propagation decayed exponentially with the social distance from the source. We show that information distortion and the overweighting of other people's errors are two individual-level mechanisms hindering judgment propagation at the scale of the chain. Our results contribute to the understanding of social-contagion processes, and our experimental method offers numerous new opportunities to study judgment propagation in the laboratory.

Using residents' worries about technology as a way of resolving environmental remediation dilemmas

The choice of technologies used to remediate contaminated environments are increasingly made via engagement with affected local residents. Despite this, little is known about how residents perceive remediation technology applications. Building on the findings of broader technology worry research, and drawing on data from a telephone survey of 2009 residents living near thirteen contaminated sites in Australia, regression analysis of closed-ended survey questions and coding analysis of open-ended survey questions are combined to identify the main predictors of worries concerning particular remediation technologies, and how worry affects them. This suggests respondents are more worried about the application of chemical remediation technologies than the application of physical and thermal technologies, which in turn caused more worry than the application of biotechnology. The paper suggests that these worries can be reduced via direct engagement with residents about remediation technologies, suggesting that such engagement can provide knowledge that improves remediation technology decisions.

Can Simple Transmission Chains Foster Collective Intelligence in Binary-Choice Tasks?

In many social systems, groups of individuals can find remarkably efficient solutions to complex cognitive problems, sometimes even outperforming a single expert. The success of the group, however, crucially depends on how the judgments of the group members are aggregated to produce the collective answer. A large variety of such aggregation methods have been described in the literature, such as averaging the independent judgments, relying on the majority or setting up a group discussion. In the present work, we introduce a novel approach for aggregating judgments—the transmission chain—which has not yet been consistently evaluated in the context of collective intelligence. In a transmission chain, all group members have access to a unique collective solution and can improve it sequentially. Over repeated improvements, the collective solution that emerges reflects the judgments of every group members. We address the question of whether such a transmission chain can foster collective intelligence for binary-choice problems. In a series of numerical simulations, we explore the impact of various factors on the performance of the transmission chain, such as the group size, the model parameters, and the structure of the population. The performance of this method is compared to those of the majority rule and the confidence-weighted majority. Finally, we rely on two existing datasets of individuals performing a series of binary decisions to evaluate the expected performances of the three methods empirically. We find that the parameter space where the transmission chain has the best performance rarely appears in real datasets. We conclude that the transmission chain is best suited for other types of problems, such as those that have cumulative properties.

Patterns of cooperation during collective emergencies in the help-or-escape social dilemma

Although cooperation is central to the organisation of many social systems, relatively little is known about cooperation in situations of collective emergency. When groups of people flee from a danger such as a burning building or a terrorist attack, the collective benefit of cooperation is important, but the cost of helping is high and the temptation to defect is strong. To explore the degree of cooperation in emergencies, we develop a new social game, the help-or-escape social dilemma. Under time and monetary pressure, players decide how much risk they are willing to take in order to help others. Results indicated that players took as much risk to help others during emergencies as they did under normal conditions. In both conditions, most players applied an egalitarian heuristic and helped others until their chance of success equalled that of the group. This strategy is less efficient during emergencies, however, because the increased time pressure results in fewer people helped. Furthermore, emergencies tend to amplify participants’ initial tendency to cooperate, with prosocials becoming even more cooperative and individualists becoming even more selfish. Our framework offers new opportunities to study human cooperation and could help authorities to better manage crowd behaviours during mass emergencies.

Crowd behaviour during high-stress evacuations in an immersive virtual environment

Understanding the collective dynamics of crowd movements during stressful emergency situations is central to reducing the risk of deadly crowd disasters. Yet, their systematic experimental study remains a challenging open problem due to ethical and methodological constraints. In this paper, we demonstrate the viability of shared three-dimensional virtual environments as an experimental platform for conducting crowd experiments with real people. In particular, we show that crowds of real human subjects moving and interacting in an immersive three-dimensional virtual environment exhibit typical patterns of real crowds as observed in real-life crowded situations. These include the manifestation of social conventions and the emergence of self-organized patterns during egress scenarios. High-stress evacuation experiments conducted in this virtual environment reveal movements characterized by mass herding and dangerous overcrowding as they occur in crowd disasters. We describe the behavioural mechanisms at play under such extreme conditions and identify critical zones where overcrowding may occur. Furthermore, we show that herding spontaneously emerges from a density effect without the need to assume an increase of the individual tendency to imitate peers. Our experiments reveal the promise of immersive virtual environments as an ethical, cost-efficient, yet accurate platform for exploring crowd behaviour in high-risk situations with real human subjects.