RUNNING HEAD: Public engagement with science and social media

PUBLIC ENGAGEMENT WITH AND COMMUNICATION OF SCIENCE IN A WEB- 2.0 MEDIA ENVIRONMENT

Sara K. Yeo Department of Communication University of Utah

All correspondence regarding this essay should be addressed to the first author in the Department of Communication, University of Utah, 2618 Languages and Communication Building, 255 South Central Campus Drive, Salt Lake City, UT 84112-0491; ph: +1-801-585-5918; e-mail: [email protected].

White paper prepared for the American Association for the Advancement of Science (AAAS) December 2015

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PREFACE

AAAS describes public engagement with science as intentional, meaningful interactions that provide opportunities for mutual learning between scientists and members of the public. Through the Alan I. Leshner Leadership Institute for Public Engagement with Science, AAAS empowers scientists and engineers to practice high-impact public engagement by fostering leaders who advocate for critical dialogue between scientists and the public and lead change to enable their communities, institutions, and others to support public engagement.

The bibliography below, with additional work on understanding mechanisms for institutional change, as well as practical experience in public engagement with science, will guide the work of the Leshner Leadership Institute, as well as other programs of the AAAS Center for Public Engagement with Science (Center).

The Center, which manages the Leshner Leadership Institute, offers this bibliography as a resource for the broader community of public engagement practitioners, researchers, and scientists doing public engagement.

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Introduction The introduction of new communication technologies has heralded a new era of communication marked by increases in media choice (made possible by technological advancements) and overall use of technology by citizens. Media are ubiquitous and a “pick-and- choose” culture has emerged (Blumler and Kavanagh, 1999, p. 218). As media options have proliferated, media have become less “mass” and more individualized (Chaffee and Metzger, 2001), yet remain essential to our daily lives; we watch television, surf the Web, listen to music, and read the news, often on a daily basis. And we do all this on multiple mobile and web-based devices, attending to any channel we choose (Pew Research Center, 2014). Additionally, media are becoming increasingly fragmented. But how do media consumption choices affect people’s dispositions toward pressing issues of science, technology, and public affairs facing society? And how can we learn from scholarship in the science of (science) communication to better communicate about STEM issues? Some scholars are concerned that media fragmentation will lead to the lack of shared contexts for message interpretation and the demise of inadvertent audiences (e.g., Bennett and Iyengar, 2008), while others find little evidence for this (e.g., Webster and Ksiazek, 2012). Others argue that many television programs such as South Park, The Simpsons, The Daily Show with Trevor Noah, and Last Week Tonight with John Oliver, while not billed as news, may still provide public affairs commentary and increase knowledge about a variety of issues (Brewer and Cao, 2006; Xenos and Becker, 2009). And while science programs such as Nova and Nature still exist, the availability of channels that contain entertainment media far outnumber science media, often leading citizens away from programs about STEM issues (Prior, 2007; Prior, 2013). Moreover, social media are becoming more popular; use of social media has increased significantly since 2005, with two-thirds of Americans adults now using at least one form of social media (Pew Research Center, 2015d). And users increasingly turn to social media for news (Pew Research Center, 2013). The use of social networking sites for information compounds the challenge of media fragmentation. In addition to a “pick-and-choose” culture, algorithms in social media (and online media more generally) “learn” from our media use habits and exacerbate our ability to cocoon ourselves in echo chambers by presenting us with information to which we are most likely to attend, i.e., that which is already consistent with our opinions and attitudes. If citizens lack common ground for discussion and interaction of scientific and public issues, polarization is a concern. The ability to encase ourselves in echo chambers reinforces our existing opinions by allowing us to be exposed only to media that are consistent with our preexisting attitudes. According to Sunstein (2007), “[w]ithout shared experiences, a heterogeneous society will have a much more difficult time in addressing social problems. People may even find it hard to understand one another. Common experiences, emphatically including the common experiences made possible by the media, provide a form of social glue” (p. 9). In other words, media fragmentation has the potential to lead to social fragmentation on a variety of issues. Indeed, fragmentation in public attitudes toward science and technology is already obvious; issues such as climate change and energy are galvanize and divide public audiences in the United States. Recent data show clear partisan differences in opinions about climate change, with 68 percent of Democrats compared to 20 percent of Republicans agreeing that it is a very serious problem (Pew Research Center, 2015a). Partisan divides over support for funding alternative energy research have also been increasing since 2008 (Pew Research Center, 2011).

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These patterns highlight trends in fragmentation and subsequent ideological polarization observed in issues of science and technology among public audiences (Baldassarri and Gelman, 2008; Evans, 2003; Gastil, Kahan, and Braman, 2006; Levendusky, 2013). Although some may assume public opinion of science and technology to be independent of political affairs, empirical data strongly suggest this is not the case (Brossard, 2013; Scheufele, 2013; Yeo, 2014). Science is increasingly embedded in society as citizens cast votes for political elites who make policy decisions related to science and technology. Scientific research, funding, and regulation are increasingly affected by politics in contemporary society. Science and technology are continually evolving and new issues frequently capture publics’ interest. As this happens, citizens will be increasingly faced with unfamiliar issues and challenged to interpret novel complex information. And as consumers move away from traditional print and broadcast media, news diets have become more varied and science information is increasingly consumed online (Anderson, Brossard, and Scheufele, 2010). As of 2012, people primarily turn to online sources for science and technology information (National Science Board, 2014). In this fragmented and interactive media environment, how scientists and other practitioners of science communication1 engage with public audiences has substantial implications. This paper seeks to review existing literature in science, risk, and environmental communication, as well as the related fields of political communication, social psychology, and science and technology studies, to answer four questions: i) How can online media be used by scientists to foster effective engagement and communication with broad non-expert audiences? ii) What online and social media “best practices” can be implemented for effective public communication of and engagement with science? iii) How can the impacts of public communication and engagement practices be measured? iv) How can scientists be more strategic about public communication via online media? To answer these questions, I review the scholarly literature on science, scientists, public audiences, and the online media environment and discuss some best practices related to communicating STEM issues and ways to measure the impacts of public communication efforts. I rely on theories from the fields of communication and psychology, among others, to inform potential best practices as there is relatively little direct scholarship in this area.

Science and the online media environment While scientists have long used the Internet for scholarly collaboration (Kouzes, Meyers, and Wulf, 1996; Murthy and Lewis, 2015), public audiences are turning to online technologies for information about science. In 2006, television was still the primary source of science news for most American publics; only 20 percent of all Americans went online for science information (Horrigan, 2006). According to the National Science Board (2014), approximately 40 percent of Americans turned to the Internet for news about science and technology in 2012. For specific information about science, the proportion of public audiences going online in the same year was the highest ever observed (63 percent; National Science Board, 2014). As individuals

1 It is important to note that the term “science” is used broadly in this essay. When discussing “science communication,” I refer not only to scientific issues, but also environmental, technological, and, sometimes, medical issues. Because of the so-called “nano-bio-info-cogno” (NBIC) convergence, many scientific issues blur the lines between environment, human health, and technology. Moreover, many of these issues, such as genetic engineering and nanotechnology, occur at the intersection of science and politics.

Public engagement with science and social media 3 increasingly turn to online media for information about STEM issues, public communication of science, particularly via Web-2.0 platforms, becomes increasingly promising pathways for promoting science in society. Web-2.0 media refer to any form of online media characterized by interaction between message sender and receiver. In other words, Web-2.0 technologies refer to interactive online media. In addition to growing acknowledgment that media are important for the formation of public opinion and attitudes on STEM issues, the nature of science has and continues to evolve, making the need for public communication as well as scholarship of public communication more acute. Some argue that controversies in science have changed little since Copernicus’ and Galileo’s theories of astronomy (Sherwood, 2011). Yet, while some aspects of scientific controversies have persisted, modern controversies tend to be accompanied by convoluted ethical, legal, and social implications (ELSI). Science has become increasingly complex and cross-disciplinary and non-expert audiences often lack the tools and frameworks necessary to rationally and critically evaluate scientific information. This “revolution” in the nature of science, termed the NBIC convergence (Khushf, 2007), has been occurring at the intersection of many scientific disciplines and is characterized by its rapid pace coupled with abundant ELSI concerns. Media and science are becoming increasingly intertwined in a process known as “medialization” (Ivanova, Schäfer, Schlichting, and Schmidt, 2013; Weingart, 1998). As publics move online for science and technology information, scientists can leverage this reciprocal relationship with media and online technologies for public communication and engagement. This relationship allows media to “rely on public scholars or celebrity scientists for newsworthy portrayals of scientific breakthroughs” (Scheufele, 2014, pp. 13585-13586) while scientists, in turn, can “take advantage of traditional and online media to increase the impact of their research beyond the finite network of academic publishing and to advocate for more public investment in science” (Scheufele, 2014, p. 13586). Though scholars recognize more research about scientists’ perceptions of online engagement is required (Besley, 2014), empirical data show scientists are willing to engage in public communication (Peters, 2013) despite long-standing and dominant negative perceptions in scientific communities (Dunwoody and Ryan, 1985). While the need for science communication is urgent, public audiences and scientists do not always see eye-to-eye or understand the same “language” (for example, see Table 1; from Somerville and Hassol, 2011). To this end, scholarship informing best practices of public communication of science is imperative, yet there remains a paucity of empirical research. Many aspects of public science communication remain uninvestigated and recommendations for best communication practices first require a brief overview of the literature in the science of science communication.

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Table 1. Terms related to global climate change that have different meanings for scientists and lay audiences (Somerville and Hassol, 2011, p. 51).

Recent scholarship in the science of science communication has attempted to elucidate the roles which media play in formation of public attitudes about STEM issues. Many aspects of this area have been studied. For example, research shows public audiences are selective about mediated scientific information and use political cues to inform their information seeking habits (Yeo, Xenos, Brossard, and Scheufele, 2015). In addition, many lay audiences use cognitive shortcuts, including religiosity (Brossard, Scheufele, Kim, and Lewenstein, 2009), deference to scientific authority (Brossard and Nisbet, 2007), and political ideology (Yeo et al., 2014), to inform their attitudes. The cognitive shortcuts, or heuristics, act as perceptual filters and facilitate interpretation of complex scientific issues. Other aspects of online communication related to STEM issues, such as how individual perceptions and attitudes are influenced by online comments, have also been studied. In particular, research shows risk perceptions of nanotechnology are influenced by a complex interaction of heuristics and incivility in online comments (Anderson, Brossard, Scheufele, Xenos, and Ladwig, 2013). Social institutions also have the potential to amplify or attenuate the effects of perceptual filters and how publics use these shortcuts to interpret science information. This risk communication framework is known as the social amplification (or attenuation) of risk framework (SARF). Media, in particular, differentially affect risk-related attitudes toward STEM issues. For example, in a recent study examining how U.S. publics responded to the Fukushima Daiichi nuclear disaster, media were found to potentially amplify and attenuate risk perceptions of nuclear power differentially, depending on respondents’ political leanings (Yeo et al., 2014). Despite the need for more science communication scholarship, the contemporary media environment is an exciting space for scientists to engage with public audiences. Indeed, there have been calls for scientists to engage with public audiences online, particularly through social media (Claussen et al., 2013; Gennaro, 2015; Taffe, 2015; Van Eperen and Marincola, 2011; Wilkins, 2008; Woodgett, 2014). Many scientists already engage with broad audiences online through weblogs (commonly known as blogs) though we should be cautious of blogs becoming

Public engagement with science and social media 5 one-way venues for experts to communicate to, instead of with, non-expert audiences (Ridge- Newman, 2011). Blogs, which some argue humanize scientists (Wilkins, 2008), have also played noteworthy roles in scientific controversies, most recently the arsenic life case involving NASA scientists (see Dr. Rosemary Redfield's blog (http://rrresearch.fieldofscience.com/); Clarkson, 2012; Yeo et al., revise and resubmit). Yet, as public communication also involves more traditional media, blogs may not provide a viable option as journalists do not perceive them to be valuable sources of information (Colson, 2011). Given the limitations of blogs and the prevalent use of social media, it is worthwhile examining online social networking platforms for scientists communicating science. Importantly, close to half of scientists associated with AAAS connect with online publics via social media, though only 27 percent report doing so occasionally or often (Pew Research Center, 2015b). Social media are central to interactive online media and their use has grown over the last decade. While social media use remains most prevalent among young adults between the ages of 18 and 29, use among older Americans (those over 65 years of age) has increased. Additionally, more than half of rural Americans use social media (Pew Research Center, 2015d). These indicators highlight the potential of social media for engagement with audiences not typically reached through traditional science outreach and communication activities. There are various types of social media, some focusing on personal connections (e.g., Facebook), while others focus on professional (academic) networks (e.g., LinkedIn, ResearchGate). Media-sharing sites such as YouTube and Instagram may also be considered social media as users create, share, and interact with content and each other. Despite differences in format, all social media share two important characteristics. First, content is created or co- created by users of the platform. Second, users can interact and discuss content with others. These characteristics, which appear to have democratized communication, are particularly interesting as comments and interactions can act as cognitive cues for interpretation of information. While professional networks such as ResearchGate (http://www.researchgate.net/) or Academia.edu (https://www.academia.edu/) may be effective ways for researchers to share and discover new scholarship, reach to public audiences is limited on these social networks. In terms of communicating science to broader non-expert audiences, two types of social media are of particular interest: Facebook and Twitter. Currently, Facebook is the most popular social networking site in the U.S. and worldwide. Seventy-one percent of online Americans (Pew Research Center, 2015c) and 65 percent of adults worldwide use this social networking site (Reuters Institute, 2015). And the most recent data show slightly over 40 percent of Facebook users, both in the U.S. (47 percent; Pew Research Center, 2013) and worldwide (41 percent; Reuters Institute, 2015), use Facebook for news consumption. While it may be more challenging to connect with public audiences on Facebook due to the nature of the platform (users have to be approved as “friends” to view content others post), its widespread use makes it an important medium to consider when deciding on communication strategies. Twitter, a microblogging platform that facilitates real-time updates, holds a lot of promise for public science communication and has recently been the focus of several studies (see Ehrenberg, 2012 for examples). Although only slightly over 20 percent of people (both worldwide and in the U.S.) use Twitter, it has become a prominent social networking site for science communication and roughly half its users in the U.S. consume news on Twitter (Pew Research Center, 2013). Currently, Twitter boasts 320 million monthly active users and its mission is “to give everyone the power to create and share ideas and information instantly,

Public engagement with science and social media 6 without barriers” (Twitter, 2015). Tweets can be categorized using hashtags (typically keywords preceded by the “#” symbol) and shared widely by users re-posting content, known as retweeting. Many scientific organizations offer social media resources (e.g., AAAS Social Media Resources can be accessed at http://membercentral.aaas.org/social) and encourage its members to tweet at annual conferences using specific hashtags (e.g., #ansmeeting for the national meeting of the American Nuclear Society). Moreover, journalists looking for breaking news are using Twitter more and more as beat and even including tweets in their reporting (Broersma and Graham, 2012; 2013).

Online and social media best practices Public engagement and communication of science via social media will undoubtedly consist of an approach that employs multiple connected platforms. This will involve having a presence on Twitter and Facebook, as well as other social media (e.g., YouTube, Instagram, blogs) that build scientists’ social media profiles. To this end, communicators will have to make decisions about which social media best fit their purposes. For example, Facebook can be used for self-branding while Twitter is employed for conversational purposes (Kietzmann, Hermkens, McCarthy, and Silvestre, 2011). Kietzmann et al. (2011) present seven “functional blocks” that aim to assist with understanding social media to develop communication strategies: (i) identity, (ii) conversations, (iii) sharing, (iv) presence, (v) relationships, (vi) reputation, and (vii) groups. These should be used when considering the social media on which to engage as these functional blocks differ for each platform (Figure 1) and scientists’ resources, particularly time, are often limited.

Figure 1. The functional blocks of social media (Kietzmann et al., 2011).

Identity. Credibility has been shown to be an important factor in public engagement and communication of science (Bromme, Thomm, and Wolf, 2015; Brossard and Nisbet, 2007; Jamieson and Hardy, 2014). Therefore, self-branding as credible sources of information is an important aspect of public communication. One way scientists have attempted to achieve

Public engagement with science and social media 7 credibility on social media is by making connections to institutions in their social media profiles (e.g., Twitter profile of Jonathan Eisen, an evolutionary biologist at the University of California, Davis). Conversations. As Kietzmann et al. (2011) point out, the speed of conversations differ on various social media. Twitter, for example, can facilitate real-time discussion of issues while other, slower-paced platforms, demand less immediate attention. Scientists often identify time constraints as a barrier to public engagement activities (Besley, 2014). Fortunately, conversations that demand immediate attention, such as those on Twitter, are often limited in other ways (in this case, by what one can convey in 140 characters), which facilitate moving such discussions to media that are less demanding of attention. Moreover, debates on social media frequently consist of more than two users. The ability to involve other experts and communicators in a discussion further reduces the burden of individual users. Sharing. Social media are inherently interactive. Sharing content can initiate discussions and lead users to want to build relationships, but there needs to be content connecting individuals on these platforms. One aspect in Internet research that is of particular interest here is viral content. Virality, or the probability that any content item will be shared online, has been found to be influenced by emotions (Berger and Milkman, 2012), particularly awe, anger, or anxiety. In addition, the likelihood of sharing content is also influenced by surprise (Derbaix and Vanhamme, 2003), a point to which we will return when discussing the SUCCESs framework. Presence. Kietzmann et al. (2011) discuss this functional block in terms of accessibility (e.g., geographic location, “online” vs. “offline” status) of other users. While this may be an important social marketing consideration for companies, this is less of an issue for scientists who have relatively little need for instantaneous interaction or to know the location of their audiences. Relationships. Relationships, on the other hand, are an important consideration for communicating STEM issues. This refers to how users are connected within a social network, which is the essence of social media. When selecting social media, it is important for scientists to consider their goals for building relationships. Drawing from social network theory (Granovetter, 1973), it is integral to consider the structure and flow of networks. The structure of a network refers to how many dyadic connections a user has and their position within any given network. For example, scientists involved in citizen science may want to create smaller networks in which their position is more central compared to those who wish to reach as many laypersons as possible. The flow of networks describes the strength of dyadic relationships, which will also be influenced by communication goals. While it seems intuitive to prefer stronger ties, weak ties have greater reach than strong ones as they often link individuals between networks (Granovetter, 1973). Reputations. On social media, users often rely on endorsements to gauge reputation. Used in this way, reputation can be a characteristic of content as well as users. Endorsements come in different forms, depending on the platform (e.g., likes on Facebook, retweets or favorites on Twitter, number of views on YouTube). One indicator of reputation and influence on social media that has developed is Klout.com (https://klout.com). A Klout score ranges from 1 to 100, measuring a user’s influence and ability to reach others (Edwards, Spence, Gentile, Edwards, and Edwards, 2013; Stevenson, 2012). For example, astrophysicist Neil deGrasse Tyson, U.S. President Barack Obama, and Justin Bieber have Klout scores of 87, 99, and 94, respectively. Importantly, recent scholarship has demonstrated that one’s Klout score can positively influence credibility (Edwards et al., 2013).

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Groups. Social media communities can be organized into groups that have different levels of openness. Some are user-created and open, while others are by invitation only. As time is often a limiting factor for public communication and engagement of science, groups can facilitate filtering of messages. For example, applications such as HootSuite (https://hootsuite.com) or TweetDeck (https://tweetdeck.twitter.com) can be used to organize messages from Twitter (Figure 2). Applications that filter and organize messages are key tools for communicators who aim to reach a large number of audience members through weak ties.

Figure 2. Screenshot of TweetDeck with user-created lists to organize tweets. Lists can also be made using the results of keyword and hashtag searches.

In order to share and engage with others via social media, scientists must first have content. To this end, in his book, Social Media for Engineers and Scientists (2012), DiPietro recommends adopting a mindset called “ABC: Always Be Collecting.” While he is primarily discussing collecting material for blogs in his book, this advice is relevant for social media. Indeed, scientists may not find the ABC mindset novel; science is continuously generating novel information and it is a natural part of a scholar’s job to keep up-to-date. Many journalists use social media itself as a source of information (Broersma and Graham, 2012; 2013), with tools like TweetDeck to help track and organize information. In addition to social media-specific

Public engagement with science and social media 9 tools, email alerts and RSS (Real Simple Syndication) feeds from academic journals can be used for content collection and curation. As media continue to evolve and communication technologies change, it is more practical to provide general best practices for communicating STEM instead of those specific to any given social media platform. To do so, I draw from Chip and Dan Heath’s book, Made to Stick (Heath and Heath, 2007) and adapt their model for our purposes. Made to Stick describes 6 principles of sticky ideas using the SUCCESs framework: Simple, Unexpected, Concrete, Credible, Emotional, and Stories. In the following paragraphs, I treat each part of this framework in turn. Simple. This principle refers to isolating the core of a message and keeping the message compact. Of the 6, this principle is likely to be the most challenging for scientists as we often feel the nuances of research and scientific findings should not be overlooked. However, it is imperative to remember this principle tasks us with identifying the most important aspect of a scientific message and keeping it succinct. Many experts suffer from what Heath and Heath (2007) refer to as the “Curse of Knowledge,” which makes it challenging for experts to convey ideas to non-expert audiences. To explain this “curse,” the authors describe an experiment in which participants were divided into “tappers” and “listeners” (Newton, 1990). Tappers finger- tapped 3 well-known songs on a table for listeners and were subsequently asked to estimate the likelihood of listeners correctly identifying the song they had just tapped. Listeners, on the other hand, were tasked with identifying the finger-tapped songs. Unsurprisingly, tappers’ predicted listener accuracy (50 percent) was much higher than actual listener accuracy (2.5 percent). The tappers as experts had “personal music accompaniment[s]” (Newton, 1990, p. 42) when tapping, causing them to overestimate the knowledge of listeners. Similarly, scientists are generally more knowledgeable than the audiences to which they are communicating. This further emphasizes the importance (and difficulty) of identifying a compact core of a message. Heath and Heath are quick to note that communicating a compact message is not equivalent to “dumbing down.” Instead, they emphasize that simple messages are “short sentences drawn from long ideas” (Heath and Heath, 2007, p. 48) and that scientists should take advantage of and tap into existing mental schema to bring complexity into compact core messages. Schema, a concept from cognitive psychology, are abstract mental frameworks or knowledge structures in memory that people use to classify and interpret information. The underlying assumption is that people are “cognitive misers” who have limited capacity for dealing with information and rely on cues and information stored in memory to form opinions (Fiske and Taylor, 1991). The public opinion scholar, Walter Lippmann, referred to these frameworks as stereotypes, arguing that humans “do not first see, and then define, we define first and then see” (Lippmann, 1922, p. 55). The copious amounts of information with which we are bombarded are filtered through these schema, enabling us to selectively (though often unconsciously) attend to and store pieces of information in groups to make sense of them (Lodge and Hamill, 1986; Lodge, McGraw, Conover, Feldman, and Miller, 1991). Grouped information stored in memory is then drawn on when making judgments and decisions. These schema, then, help us form the “pictures inside [our] heads” (Lippmann, 1922, p. 18), i.e. our opinions. In the field of communication, schema theory has been used most in studying framing effects (Cacciatore, Scheufele, and Iyengar, 2015; Scheufele, 1999; Scheufele and Tewksbury, 2007). In science communication research, scholars have used mental schema to examine information seeking (Jang, 2014; Yeo et al., 2015), processing (Kim, Yeo, Brossard, Scheufele, and Xenos, 2014), and public attitudes toward science (Binder, Cacciatore, Scheufele, Shaw, and Corley, 2012; Gauchat, 2015; Nisbet and Markowitz, 2014). Schema inherently simplify

Public engagement with science and social media 10 complicated issues and STEM topics have been framed in many ways that tap into people’s existing schema. Examples include framing stem cell research as “scientists playing God” or Greenpeace’s campaign against genetically modified foods (GMOs) featuring “FrankenTony,” a fictional version of the Kellogg’s Frosted Flakes cereal mascot, Tony the Tiger. The latter example activates individuals’ schemas, ranging from “playing God” to “artificial, created” foods (Nisbet and Scheufele, 2007). Understanding what schema might be activated when framing a scientific issue is an important part of a “simple” message. Unexpected. The second principle is about attracting and retaining attention; these can be accomplished by violating a familiar pattern and creating an “information gap,” respectively. To attract attention, scientists need to determine what is counterintuitive or surprising about their message. Heath and Heath (2007) refer to this as “first-level unexpectedness” and recommend taking advantage of surprise to grab attention. “Second-level unexpectedness” facilitates the retention of attention and can be accomplished using curiosity. Here, Heath and Heath appeal to the gap theory of curiosity (Loewenstein, 1994). By creating a gap between what a person knows and what she wishes to know (information gap),2 curiosity becomes a powerful motivator that can stimulate sustained interest. Research on interest in science has primarily been conducted in the context of science education (for a review of research of interest in science, see Krapp and Prenzel, 2011) though scholars have recognized the need for multifaceted approaches to public engagement (Feinstein, 2015). Scientists may find it relatively easy to maintain interest once they have caught the attention of their audience. Scientific research is inherently investigative and often has an element of mystery that can serve to stimulate curiosity by creating an information gap that communicators should use to their advantage. Concrete. People are better able to create “pictures inside their heads” from concrete ideas. Indeed, one main difference between experts and non-experts is the ability to think in abstract terms. Again, making ideas concrete is not equivalent to “dumbing down.” Instead, concrete ideas are ones that are described in a way that both laypersons and experts understand. To this end, identifying and understanding one’s audience is an important part of public communication and engagement. Understanding the audiences with which one is engaging ensures that communications can be designed to leverage appropriate cognitive schema that help people interpret a message. Credible. The fourth principle in the SUCCESs framework is related to the Identity functional block (Kietzmann et al., 2011). Scholars have shown that credibility is an important factor for public attitudes and opinions toward science (Jamieson and Hardy, 2014). Thus, by clarifying affiliations to trusted institutions or organizations, scientists can leverage external credibility to convey messages for positive outcomes. We also tend to make ideas and concepts credible through the use of empirical data, often in the form of statistics. While this represents a form of internal credibility, it is vital to communicate empirical data on a human scale, i.e., in a relatable form for non-experts. Moreover, research in risk communication has found perceptions of risk to be influenced by whether statistics are communicated as probabilities (20 percent) or frequencies (2 in 10) (Slovic, Finucane, Peters, and MacGregor, 2004; Slovic, Monahan, and MacGregor, 2000). Scientists (as well as other communicators), then, should make deliberate choices about form and scale when using empirical data for public communication and engagement. Suggestions for best practices of reporting statistical data include using consistent

2 Heath and Heath (2007) refer to this as a “knowledge gap.” I use “information gap” in this essay to distinguish this from the knowledge gap theory in communication that describes gaps in publics’ knowledge acquisition due to socioeconomic inequalities in access to information resources (Tichenor, Donohue, and Olien, 1970).

Public engagement with science and social media 11 formats (e.g., frequencies, probabilities, percentages), a denominator of base 10 where possible (e.g., 1 in 10, 30 in 100), and avoiding the use of decimals (Lipkus, 2007). Emotional. Scholarship in cognitive and social psychology, as well as political science and public opinion, show that our thinking is affected by emotion to some extent (Lodge and Taber, 2013). As a result, concepts and messages that appeal to emotion and affect tend to be more “sticky” (Heath and Heath, 2007). In Made to Stick, the authors suggest two ways to make messages appeal to affect. First, scientists can appeal to self-interest. For example, when communicating about climate change, can frames that evoke personal health incentives for sustainable behaviors be used? Another way to create affect-laden messages is to appeal to identity. Much research has focused on how individual judgments and attitudes are affected by social norms (Campo, Cameron, Brossard, and Frazer, 2004; Turcanu, Perko, and Laes, 2013; van der Linden, 2015). In fact, socio-cultural influences have been shown to have strong effects on perceptions of risk of climate change (van der Linden, 2015). Stories. The last principle highlights the importance of narratives for public engagement with science. Narratives can capture and retain the attention of audiences, the latter by creating information gaps, as well as convey clear messages that make science relevant to people’s lives (Downs, 2014). Narratives have been found to have significant impacts on public attitudes (Leiserowitz, 2004; Lowe et al., 2006; Spoel, Goforth, Cheu, and Pearson, 2009). For example, the 2004 film portraying catastrophic events related to climate change, The Day After Tomorrow, impacted a variety of outcomes among people who viewed the movie, ranging from risk perception to policy preferences (Leiserowitz, 2004). Other scholars found impacts of the movie on behavioral intentions (Lowe et al., 2006). However, Lowe et al. (2006) noted that the dramatized depiction in The Day After Tomorrow also desensitized audiences, thus reducing their belief in the likelihood of extreme events. In an essay describing challenges faced by a collaborative science communication effort, Wong-Parodi and Strauss (2014) document solutions that abide by the principles of the SUCCESs model. Ultimately, recommendations of best practices in science communication must emphasize the need for data. Several of the 6 principles described above emphasize the need to be familiar with one’s audience on various dimensions. In this regard, it is imperative that communicators rely on data, instead of intuition, to design messages.

Impacts of communication and public engagement Currently, there are few tools scientists can use to assess their social media impact. One way to measure impact is to use key performance indicators, metrics that are “central to the wellbeing of the organization” (Sterne, 2010, p. 4). While these have been applied primarily to social marketing, key performance indicators may be valuable in assessing particular goals of scientists’ public engagement efforts. Necessarily, scientists will have to identify the goals of their efforts in order to evaluate them. Neiger et al. (2012) identify four key indicators for social media use in health promotion: insight, exposure, reach, and engagement. Insight refers to information about audience perspectives and attitudes obtained from social media (e.g., opinions expressed on Twitter). Exposure refers to the extent a message is viewed and is typically measured by enumerating clicks, while reach is a measure of the number of people who have had contact with the message as measured by likes (a person can view content without liking it), among other metrics. Engagement links social media content to individual actions that can range from commenting on

Public engagement with science and social media 12 a message to sharing it. Depending on the priority of each indicator, different metrics should be used for evaluation. Many social media users also measure impact through influence as quantified by Klout scores. Other ways to measure impact include first identifying the communication or engagement goals and using platform-specific metrics. For example, to measure reach and engagement on Twitter, you might enumerate retweets and replies or conversations, respectively. On other forms of social media, page views and likes may be useful metrics, depending on communication goals. Social media analytics tools, such as Google Analytics or tools provided by HootSuite, allow tracking of social media impact.3 Scientists may also be interested in the outcomes of their public engagement efforts within the realm of academia. Research in this area is relatively new and inconclusive. Some allude to the benefits to research of an online presence (Bik and Goldstein, 2013). Other studies have examined more direct impacts of social media. Tweets have been found to predict citations over a limited period of time (Eysenbach, 2011), though others have found little correlation between citations and tweets (Haustein, Peters, Sugimoto, Thelwall, and Larivière, 2013), and when combined with traditional methods of engagement (e.g., interacting with journalists) have the potential to amplify scholarly impact (Liang et al., 2014). Other advantages of an online presence include finding a job (Quinnell, 2011), improved writing skills (Heap and Minocha, 2012), and having a community to share and refine ideas (Darling, Shiffman, Côté, and Drew, 2013). Undoubtedly, more research needs to be conducted on both direct and, importantly, indirect impacts of public communication and engagement efforts for scientists. While assessing individual scientists’ engagement impacts is important, it is equally important to consider how social media can be used for broader outcomes and goals, such as nurturing trust, awareness, and appreciation of science, encouraging public decision-making based on data, encouraging dialog about science in society, and influencing policy agendas and public action on STEM issues. Unfortunately, while scholars recognize the value of communication efforts online (e.g., Brossard, 2013), there is little empirical research on the impacts of social media communication and engagement on outcomes such as these. This paucity has not gone unnoticed, however, as evidenced by the calls for empirical research in this area (Brossard, 2013; Regenberg, 2010; Stilgoe, Lock, and Wilsdon, 2014). One of the many challenges for science communication scholars is the pace at which social media evolve. Empirical research often struggles to keep up with the rapid pace of communication technology, though scholars continue to investigate these issues. There are few examples of such research, though not specific to social media, focused on trust in scientists, broadly construed as trust in scientists as sources of information and embodiments of science. Trust has been identified as a necessary condition for delivering successful messages about STEM issues (Dahlstrom, 2014). Indeed, levels of trust and how STEM issues are framed strongly affect public support (e.g., Bolsen, Druckman, and Cook, 2014). Trust, and the related concept of credibility, has been shown to be determined by perceptions of knowledge and expertise, honesty and openness, and perceptions of concern and care (Peters, Covello, and McCallum, 1997). Scientists may be able to cultivate these perceptions among non-expert audiences through the use of social media, thus positively affecting public engagement outcomes. First, perceptions of knowledge and expertise may be increased by drawing on aforementioned external and internal credibility best practices. Second, through engaging with public audiences using

3 A list of social media analytics tools can be found at https://blog.bufferapp.com/social-media-analytics-tools.

Public engagement with science and social media 13 interactive online media, scientists are humanized (for example, see the Twitter hashtag “#thisiswhatascientistlookslike,” which aims to bring awareness to diversity issues in STEM but also serves to give audiences a more realistic picture of scientists), which may in turn increase perceptions of care. Lastly, research has shown that communicating uncertainty may not necessarily have a detrimental effect (Retzbach and Maier, 2014), though this likely depends on the issue at hand. Communicating uncertainty in the context of climate change, for example, has had negative policy effects (Ding, Maibach, Zhao, Roser-Renouf, and Leiserowitz, 2011). Still, communicating uncertainty may serve to increase audiences’ perceptions of scientists’ openness and honesty. Despite the need for more scholarship in many aspects of science communication, particularly on social media best practices and how social media impact public engagement outcomes, it is clear that public communication of and engagement with science is imperative. While some scientists can and will communicate with public audiences, it is not reasonable to expect all scientists to participate in this effort. Nor is this necessary. This creates a niche for communicators of science who understand the science of science communication, thus facilitating effective public engagement of science, as well as empirically-driven assessment of these efforts.

Public engagement with science and social media 14

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