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

An integrative framework for mapping the psychological landscape of risk perception

We vary greatly in our perception of risk, not just because of differences between risks themselves, but also because of individual, contextual and cultural differences too. To better understand and predict responses to risk, we need to (a) integrate these components, combining approaches from different psychological disciplines and (b) also consider risk tolerance - how individuals trade-off between risks and benefits. We therefore developed an ICONS (individual, contextual, cognitive, social) framework; using it across two empirical studies (n = 4228) to examine how individuals perceive and respond to the quotidian risks associated with consumer products. Three dimensions underlined risk perceptions: benefits, dread and individual responsibility. Risk tolerance was typically predicted by interactions between individual (demographic, cultural worldview, personality) and contextual (product type/category, harm information) factors. In turn, perceived dread, benefits and individual differences shaped how likely participants were to communicate risk information. Our results demonstrate for the first time how the interaction between individual, cognitive (risk tolerance, intensity), contextual, and social (risk communication) factors is key to understanding and predicting risk perceptions. Together, our findings help explain why societal responses to risks are often difficult to predict and have implications for the spread, and amplification, of risk information.

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.

Sociotechnical Considerations About Ocean Carbon Dioxide Removal

Ocean carbon dioxide removal (OCDR) is rapidly attracting interest, as climate change is putting ecosystems at risk and endangering human communities globally. Due to the centrality of the ocean in the global carbon cycle, augmenting the carbon sequestration capacity of the ocean could be a powerful mechanism for the removal of legacy excess emissions. However, OCDR requires careful assessment due to the unique biophysical characteristics of the ocean and its centrality in the Earth system and many social systems. Using a sociotechnical system lens, this review identifies the sets of considerations that need to be included within robust assessments for OCDR decision-making. Specifically, it lays out the state of technical assessments of OCDR approaches along with key financial concerns, social issues (including public perceptions), and the underlying ethical debates and concerns that would need to be addressed if OCDR were to be deployed as a carbon dioxide removal strategy.

Cognitive Networks Extract Insights on COVID-19 Vaccines from English and Italian Popular Tweets: Anticipation, Logistics, Conspiracy and Loss of Trust

Monitoring social discourse about COVID-19 vaccines is key to understanding how large populations perceive vaccination campaigns. This work reconstructs how popular and trending posts framed semantically and emotionally COVID-19 vaccines on Twitter. We achieve this by merging natural language processing, cognitive network science and AI-based image analysis. We focus on 4765 unique popular tweets in English or Italian about COVID-19 vaccines between December 2020 and March 2021. One popular English tweet contained in our data set was liked around 495,000 times, highlighting how popular tweets could cognitively affect large parts of the population. We investigate both text and multimedia content in tweets and build a cognitive network of syntactic/semantic associations in messages, including emotional cues and pictures. This network representation indicates how online users linked ideas in social discourse and framed vaccines along specific semantic/emotional content. The English semantic frame of “vaccine” was highly polarised between trust/anticipation (towards the vaccine as a scientific asset saving lives) and anger/sadness (mentioning critical issues with dose administering). Semantic associations with “vaccine,” “hoax” and conspiratorial jargon indicated the persistence of conspiracy theories and vaccines in extremely popular English posts. Interestingly, these were absent in Italian messages. Popular tweets with images of people wearing face masks used language that lacked the trust and joy found in tweets showing people with no masks. This difference indicates a negative effect attributed to face-covering in social discourse. Behavioural analysis revealed a tendency for users to share content eliciting joy, sadness and disgust and to like sad messages less. Both patterns indicate an interplay between emotions and content diffusion beyond sentiment. After its suspension in mid-March 2021, “AstraZeneca” was associated with trustful language driven by experts. After the deaths of a small number of vaccinated people in mid-March, popular Italian tweets framed “vaccine” by crucially replacing earlier levels of trust with deep sadness. Our results stress how cognitive networks and innovative multimedia processing open new ways for reconstructing online perceptions about vaccines and trust.

The risk perception of nanotechnology: evidence from twitter

Nanotechnology governance, particularly in relation to human and environmental concerns, remains a contested domain. In recent years, the creation of both a risk governance framework and council has been actively pursued. Part of the function of a governance framework is the communication to external stakeholders. Existing descriptions on the public perceptions of nanotechnology are generally positive with the attendant economic and societal benefits being forefront in that thinking. Debates on nanomaterials' risk tend to be dominated by expert groupings while the general public is largely unaware of the potential hazards. Communicating via social media has become an integral part of everyday life facilitating public connectedness around specific topics that was not feasible in the pre-digital age. When civilian passive stakeholders become active their frustration can quickly coalesce into a campaign of resistance, and once an issue starts to develop into a campaign it is difficult to ease the momentum. Simmering discussions with moderate local attention can gain international exposure resulting in pressure and it can, in some cases, quickly precipitate legislative action and/or economic consequences. This paper highlights the potential of such a runaway, twitterstorm. We conducted a sentiment analysis of tweets since 2006 focusing on silver, titanium and carbon-based nanomaterials. We further examined the sentiment expressed following the decision by the European Food Safety Authority (EFSA) to phase out the food additive titanium dioxide (E 171). Our analysis shows an engaged, attentive public, alert to announcements from industry and regulatory bodies. We demonstrate that risk governance frameworks, particularly the communication aspect of those structures must include a social media blueprint to counter misinformation and alleviate the potential impact of a social media induced regulatory and economic reaction.

The number of positive, negative and neutral tweets relating to silver, carbon and titanium nanoparticles since 2006. Over a quarter of a million tweets were analyzed using a sentiment analysis methodology.

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.

Risk sharing on Twitter: Social amplification and attenuation of risk in the early stages of the COVID-19 pandemic

Social media trust and sharing behaviors have considerable implications on how risk is being amplified or attenuated at early stages of pandemic outbreaks and may undermine subsequent risk communication efforts. A survey conducted in February 2020 in the United States examined factors affecting information sharing behaviors and social amplification or attenuation of risk on Twitter among U.S. citizens at the early stage of the COVID-19 outbreak. Building on the social amplification of risk framework (SARF), the study suggests the importance of factors such as online discussion, information seeking behaviors, blame and anger, trust in various types of Twitter accounts and misinformation concerns in influencing the spread of risk information during the incipient stages of a crisis when the publics rely primarily on social media for information. An attenuation of risk was found among the US public, as indicated by the overall low sharing behaviors. Findings also imply that (dis)trust and misinformation concerns on social media sources, and inconsistencies in early risk messaging may have contributed to the attenuation of risk and low risk knowledge among the US publics at the early stage of the outbreak, further problematizing subsequent risk communication efforts.

Communicating Air Quality Index Information: Effects of Different Styles on Individuals' Risk Perception and Precaution Intention

Air Quality Index (AQI) is information about atmospheric pollutants, which is essential for governments to inform the public about the current air quality and potential health risks. By analyzing the AQIs from 11 countries (regions), we discovered considerable variations in the design of AQI information, which may open up room for unintended interpretation from the public. Therefore, as an attempt to address the inefficiency of some common styles of AQI information in promoting the public's precaution against bad air and better design such information, an online experiment with a 2 (descriptor: neutral vs. negatively valenced) × 2 (target groups in AQI warning messages: vague vs. specific) factorial design was conducted to test the effects of such information on individuals' risk perception and precaution intention. The results indicated that AQI information with a neutral descriptor was associated with lower self-risk perception and precaution intention levels than with a negatively valenced one. Among the individuals not included in the at-risk groups, those who read the warning messages with vague target groups had a higher third-person perception toward smog risk than those targeting specific population groups. Practical and theoretical implications are discussed.

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.

Risk Analysis: Celebrating the Accomplishments and Embracing Ongoing Challenges

As part of the celebration of the 40th anniversary of the Society for Risk Analysis and Risk Analysis: An International Journal, this essay reviews the 10 most important accomplishments of risk analysis from 1980 to 2010, outlines major accomplishments in three major categories from 2011 to 2019, discusses how editors circulate authors' accomplishments, and proposes 10 major risk-related challenges for 2020-2030. Authors conclude that the next decade will severely test the field of risk analysis.

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.

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.

Americans' Views of Voluntary Protective Actions Against Zika Infection: Conceptual and Measurement Issues

Understanding factors affecting decisions by people to protect themselves, or not, is critical to designing supportive communications. Here, threat, protective-action, and stakeholder perceptions were evaluated for effects on mainland Americans' behavioral intentions regarding Zika in April 2017, as postulated by the Protective Action Decision Model. Although all three perception types (including a novel resource sufficiency measure) affected intentions, these relationships varied widely depending upon the method used to measure adoption of actions (e.g., total count of all behaviors adopted vs. behavior-specific analyses), the behaviors involved, and whether analysis focused on the full sample or only on people who had a reasonable opportunity to enact the behavior or who believed it relevant to their lives. There was a general contrast between mosquito control actions (removal of mosquito breeding areas and pesticide spraying) and travel-related behaviors (avoiding travel to areas of local transmission of the virus, protecting oneself from mosquito bites after potential exposure, and practicing safe sex after potential exposure). Reported action or inaction during the 2016 mosquito season, and stages of behavior change, were both elicited in January-February 2017; both drove intentions in April 2017 for the upcoming season, although direct and indirect effects varied widely. Collectively these findings present theoretical, measurement, and practical implications for understanding, tracking, and promoting voluntary protective actions against hazards.

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.