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.

Cutting Through the Noise: Predictors of Successful Online Message Retransmission in the First 8 Months of the COVID-19 Pandemic.

In this paper, we investigate how message construction, style, content, and the textual content of embedded images impacted message retransmission over the course of the first 8 months of the coronavirus disease 2019 (COVID-19) pandemic in the United States. We analyzed a census of public communications (n = 372,466) from 704 public health agencies, state and local emergency management agencies, and elected officials posted on Twitter between January 1 and August 31, 2020, measuring message retransmission via the number of retweets (ie, a message passed on by others), an important indicator of engagement and reach. To assess content, we extended a lexicon developed from the early months of the pandemic to identify key concepts within messages, employing it to analyze both the textual content of messages themselves as well as text included within embedded images (n = 233,877), which was extracted via optical character recognition. Finally, we modelled the message retransmission process using a negative binomial regression, which allowed us to quantify the extent to which particular message features amplify or suppress retransmission, net of controls related to timing and properties of the sending account. In addition to identifying other predictors of retransmission, we show that the impact of images is strongly driven by content, with textual information in messages and embedded images operating in similar ways. We offer potential recommendations for crafting and deploying social media messages that can "cut through the noise" of an infodemic.

Longitudinal Risk Communication: A Research Agenda for Communicating in a Pandemic.

In this paper, we present a research agenda for longitudinal risk communication during a global pandemic. Starting from an understanding that traditional approaches to risk communication for epidemics, crises, and disasters have focused on short-duration events, we acknowledge the limitations of existing theories, frameworks, and models for both research and practice in a rapidly changing communication environment. We draw from scholarship in communication, sociology, anthropology, public health, emergency management, law, and technology to identify research questions that are fundamental to the communication challenges that have emerged under the threat of COVID-19. We pose a series of questions focused around 5 topics, then offer a catalog of prior research to serve as points of departure for future research efforts. This compiled agenda offers guidance to scholars engaging in practitioner-informed research and provides risk communicators with a set of substantial research questions to guide future knowledge needs.

The Frontiers of Uncertainty Estimation in Interdisciplinary Disaster Research and Practice.

Conceptualizing, assessing, and managing disaster risks involve collecting and synthesizing pluralistic information-from natural, built, and human systems-to characterize disaster impacts and guide policy on effective resilience investments. Disaster research and practice, therefore, are highly complex and inherently interdisciplinary endeavors. Characterizing the uncertainties involved in interdisciplinary disaster research is imperative, since misrepresenting uncertainty can lead to myopic decisions and suboptimal societal outcomes. Efficacious disaster mitigation should, therefore, explicitly address the uncertainties associated with all stages of hazard modeling, preparation, and response. However, uncertainty assessment and communication in the context of interdisciplinary disaster research remain understudied. In this "Perspective" article, we argue that in harnessing interdisciplinary methods and diverse data types in disaster research, careful deliberations on assessing Type III and Type IV errors are imperative. Additionally, we discuss the pathologies in frequentist approaches, calling for an increasing role for Bayesian methods in uncertainty estimations. Moreover, we discuss the potential tradeoffs associated with information and uncertainty, calling for deliberate consideration of the role of diversity of information prior to setting the scope in interdisciplinary modeling. Future research guided by further reflections on the ideas raised in this article could help push the frontiers of uncertainty estimation in interdisciplinary hazard research and practice.

#Ebola: Emergency Risk Messages on Social Media.

Public health threats require effective communication. Evaluating effectiveness during a situation that requires emergency risk communication is difficult, however, because these events require an immediate response and collecting data may be secondary to more immediate needs. In this article, we draw on research analyzing the effectiveness of social media messages during times of imminent threat and research analyzing the emergency risk communication conceptual model in order to propose a method for evaluating emergency risk communication on social media. We demonstrate this method by evaluating 2,915 messages sent by local, state, and federal public health officials during the 2014 Ebola outbreak in the United States. The results provide empirical support for emergency risk communication and identify message strategies that have the potential to increase exposure to official communication on social media during future public health threats.

The First 60 Days: American Public Health Agencies' Social Media Strategies in the Emerging COVID-19 Pandemic.

In this paper, we capture, identify, and describe the patterns of longitudinal risk communication from public health communicating agencies on Twitter during the first 60 days of the response to the novel coronavirus disease 2019 (COVID-19) pandemic. We collected 138,546 tweets from 696 targeted accounts from February 1 to March 31, 2020, employing term frequency-inverse document frequency to identify keyword hashtags that were distinctive on each day. Our team conducted inductive content analysis to identify emergent themes that characterize shifts in public health risk communication efforts. As a result, we found 7 distinct periods of communication in the first 60 days of the pandemic, each characterized by a differing emphasis on communicating information, individual and collection action, sustaining motivation, and setting social norms. We found that longitudinal risk communication in response to the COVID-19 pandemic shifted as secondary threats arose, while continuing to promote pro-social activities to reduce impact on vulnerable populations. Identifying patterns of risk communication longitudinally allows public health communicators to observe changes in topics and priorities. Observations from the first 60 days of the COVID-19 pandemic prefigures ongoing messaging needs for this event and for future disease outbreaks.

COVID-19: Retransmission of official communications in an emerging pandemic.

As the most visible face of health expertise to the general public, health agencies have played a central role in alerting the public to the emerging COVID-19 threat, providing guidance for protective action, motivating compliance with health directives, and combating misinformation. Social media platforms such as Twitter have been a critical tool in this process, providing a communication channel that allows both rapid dissemination of messages to the public at large and individual-level engagement. Message dissemination and amplification is a necessary precursor to reaching audiences, both online and off, as well as inspiring action. Therefore, it is valuable for organizational risk communication to identify strategies and practices that may lead to increased message passing among online users. In this research, we examine message features shown in prior disasters to increase or decrease message retransmission under imminent threat conditions to develop models of official risk communicators' messages shared online from February 1, 2020-April 30, 2020. We develop a lexicon of keywords associated with risk communication about the pandemic response, then use automated coding to identify message content and message structural features. We conduct chi-square analyses and negative binomial regression modeling to identify the strategies used by official risk communicators that respectively increase and decrease message retransmission. Findings show systematic changes in message strategies over time and identify key features that affect message passing, both positively and negatively. These results have the potential to aid in message design strategies as the pandemic continues, or in similar future events.

Celebrity Cancer on Twitter: Mapping a Novel Opportunity for Cancer Prevention.

Social media platforms have the potential to facilitate the dissemination of cancer prevention and control messages following celebrity cancer diagnoses. However, cancer communicators have yet to systematically leverage these naturally occurring interventions on social media as these events are difficult to identify as they are unfolding and little research has analyzed their effect on social media conversations. In this study, we add to the research by analyzing how a celebrity cancer announcement influenced Twitter conversations in terms of the volume of social media messages and the type of content. Over a 9-day period, during which actor Ben Stiller announced that he had been treated for prostate cancer, we collected 1.2 million Twitter messages about cancer. We conducted automated content analyses to identify how often common cancer sites (prostate, breast, colon, or lung) were discussed. Then, we used manual content analysis on a sample of messages to identify cancer continuum content (awareness, prevention, early detection, diagnosis, treatment, survivorship, and end of life). Chi-square analyses were implemented to evaluate changes in cancer site and cancer continuum content before and after the announcement. We found that messages related to prostate cancer increased significantly more than expected for 2 days following Stiller's announcement. However, the number of cancer messages that described other cancer locations either did not increase or did not increase by the same magnitude. In terms of message content, results showed larger than expected increases in diagnosis messages. These results suggest opportunities to shape social media conversations following celebrity cancer announcements and increase prevention and early detection messages.

Retweeting Risk Communication: The Role of Threat and Efficacy.

Social media platforms like Twitter and Facebook provide risk communicators with the opportunity to quickly reach their constituents at the time of an emerging infectious disease. On these platforms, messages gain exposure through message passing (called "sharing" on Facebook and "retweeting" on Twitter). This raises the question of how to optimize risk messages for diffusion across networks and, as a result, increase message exposure. In this study we add to this growing body of research by identifying message-level strategies to increase message passing during high-ambiguity events. In addition, we draw on the extended parallel process model to examine how threat and efficacy information influence the passing of Zika risk messages. In August 2016, we collected 1,409 Twitter messages about Zika sent by U.S. public health agencies' accounts. Using content analysis methods, we identified intrinsic message features and then analyzed the influence of those features, the account sending the message, the network surrounding the account, and the saliency of Zika as a topic, using negative binomial regression. The results suggest that severity and efficacy information increase how frequently messages get passed on to others. Drawing on the results of this study, previous research on message passing, and diffusion theories, we identify a framework for risk communication on social media. This framework includes four key variables that influence message passing and identifies a core set of message strategies, including message timing, to increase exposure to risk messages on social media during high-ambiguity events.

Lung Cancer Messages on Twitter: Content Analysis and Evaluation.

PURPOSE: The aim of this project was to describe and evaluate the levels of lung cancer communication across the cancer prevention and control continuum for content posted to Twitter during a 10-day period (September 30 to October 9) in 2016. METHODS: Descriptive and inferential statistics were used to identify relationships between tweet characteristics in lung cancer communication on Twitter and user-level data. Overall, 3,000 tweets published between September 30 and October 9 were assessed by a team of three coders. Lung cancer-specific tweets by user type (individuals, media, and organizations) were examined to identify content and structural message features. The study also assessed differences by user type in the use of hashtags, directed messages, health topic focus, and lung cancer-specific focus across the cancer control continuum. RESULTS: Across the universe of lung cancer tweets, the majority of tweets focused on treatment and the use of pharmaceutical and research interventions, followed by awareness and prevention and risk topics. Among all lung cancer tweets, messages were most consistently tweeted by individual users, and personal behavioral mobilizing cues to action were rare. CONCLUSIONS: Lung cancer advocates, as well as patient and medical advocacy organizations, with an interest in expanding the reach and effectiveness of social media efforts should monitor the topical nature of public tweets across the cancer continuum and consider integrating cues to action as a strategy to increase engagement and behavioral activation pertaining to lung cancer reduction efforts.

A cross-hazard analysis of terse message retransmission on Twitter.

For decades, public warning messages have been relayed via broadcast information channels, including radio and television; more recently, risk communication channels have expanded to include social media sites, where messages can be easily amplified by user retransmission. This research examines the factors that predict the extent of retransmission for official hazard communications disseminated via Twitter. Using data from events involving five different hazards, we identity three types of attributes--local network properties, message content, and message style--that jointly amplify and/or attenuate the retransmission of official communications under imminent threat. We find that the use of an agreed-upon hashtag and the number of users following an official account positively influence message retransmission, as does message content describing hazard impacts or emphasizing cohesion among users. By contrast, messages directed at individuals, expressing gratitude, or including a URL were less widely disseminated than similar messages without these features. Our findings suggest that some measures commonly taken to convey additional information to the public (e.g., URL inclusion) may come at a cost in terms of message amplification; on the other hand, some types of content not traditionally emphasized in guidance on hazard communication may enhance retransmission rates.

What it Takes to Get Passed On: Message Content, Style, and Structure as Predictors of Retransmission in the Boston Marathon Bombing Response.

Message retransmission is a central aspect of information diffusion. In a disaster context, the passing on of official warning messages by members of the public also serves as a behavioral indicator of message salience, suggesting that particular messages are (or are not) perceived by the public to be both noteworthy and valuable enough to share with others. This study provides the first examination of terse message retransmission of official warning messages in response to a domestic terrorist attack, the Boston Marathon Bombing in 2013. Using messages posted from public officials' Twitter accounts that were active during the period of the Boston Marathon bombing and manhunt, we examine the features of messages that are associated with their retransmission. We focus on message content, style, and structure, as well as the networked relationships of message senders to answer the question: what characteristics of a terse message sent under conditions of imminent threat predict its retransmission among members of the public? We employ a negative binomial model to examine how message characteristics affect message retransmission. We find that, rather than any single effect dominating the process, retransmission of official Tweets during the Boston bombing response was jointly influenced by various message content, style, and sender characteristics. These findings suggest the need for more work that investigates impact of multiple factors on the allocation of attention and on message retransmission during hazard events.

Terse messaging and public health in the midst of natural disasters: the case of the Boulder floods.

Social media are quickly becoming the channel of choice for disseminating emergency warning messages. However, relatively little data-driven research exists to inform effective message design when using these media. The present study addresses that void by examining terse health-related warning messages sent by public safety agencies over Twitter during the 2013 Boulder, CO, floods. An examination of 5,100 tweets from 52 Twitter accounts over the course of the 5-day flood period yielded several key conclusions and implications. First, public health messages posted by local emergency management leaders are most frequently retweeted by organizations in our study. Second, emergency public health messages focus primarily on drinking water in this event. Third, terse messages can be designed in ways that include imperative/instructional and declarative/explanatory styles of content, both of which are essential for promoting public health during crises. These findings demonstrate that even terse messages delivered via Twitter ought to provide information about the hazard event, its impact, and actionable instructions for self-protection.

An exploratory comparison of disasters, riots and terrorist acts.

One question that emerged following the 11 September attacks was how to categorise and classify the event within existing disaster and conflict-event research frameworks. A decade ago, Quarantelli (1993) compared findings on the similarities and differences between consensus- and conflict-type events by illustrating a conceptual distinction between the two. In this paper, this discussion is expanded to include terrorist attacks by offering comparisons from research findings following 11 September. We provide analyses of individual, organisational, and community-level behaviour in crisis situations and suggest how 11 September is both similar to, and differs from, consensus- and conflict-type events as they were previously considered. Applications for emergency management are also suggested.