Handbook of Research on Citizen Engagement and

Handbook of Research on Citizen Engagement and Public Participation in the Era of New Media Marco Adria University of Alberta, Canada Yuping Mao California State University Long Beach, USA

A volume in the Advances in Public Policy and Administration (APPA) Book Series

Published in the United States of America by IGI Global Information Science Reference (an imprint of IGI Global) 701 E. Chocolate Avenue Hershey PA, USA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.igi-global.com Copyright © 2017 by IGI Global. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark.

Library of Congress Cataloging-in-Publication Data

Names: Adria, Marco L., 1959- editor. | Mao, Yuping, editor. Title: Handbook of research on citizen engagement and public participation in the era of new media / Marco Adria and Yuping Mao, editors. Description: Hershey : Information Science Reference, [2016] | Series: Advances in public policy and administration | Includes bibliographical references and index. Identifiers: LCCN 2016037301| ISBN 9781522510819 (hardcover) | ISBN 9781522510826 (ebook) Subjects: LCSH: Social media--Research. | Social participation. | Citizenship. Classification: LCC HM742 .H355 2016 | DDC 302.23/1--dc23 LC record available at https://lccn.loc.gov/2016037301 This book is published in the IGI Global book series Advances in Public Policy and Administration (APPA) (ISSN: Pending; eISSN: Pending)

British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library. All work contributed to this book is new, previously-unpublished material. The views expressed in this book are those of the authors, but not necessarily of the publisher. For electronic access to this publication, please contact: [email protected].

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Chapter 4

Old Media, New Media, and Public Engagement with Science and Technology Yulia A. Strekalova University of Florida, USA

Rachel E. Damiani University of Florida, USA

Janice L. Krieger University of Florida, USA

Sriram Kalyanaraman University of Florida, USA

Daisy Zhe Wang University of Florida, USA

ABSTRACT Mass media are, collectively, an effective mechanism for the engagement of the general public in a debate and exchange of information related to science and technology innovations. Whether the aim is to affect change at the individual, population, or policy-making level, public understanding of science and interaction between experts and lay audiences are paramount. This chapter describes a case study of a cybersecurity forum that provided an opportunity for information technology experts to share their knowledge with studio and social media audiences. Reviewing conceptual and practical implications of the case study, the chapter discusses how public engagement efforts could capitalize on the strength of both traditional and online media and introduce interactive programs that cross these two media spaces.

INTRODUCTION Science and technology innovations lead to the enhanced well-being of the general public but can also cause harms. For example, the Internet facilitates many daily activities for private citizens and organizations while simultaneously increases the risk of a cyber attack that may threaten their privacy and the security of their data. Greater public involvement in the dialog about modern technologies is necessary to take the most benefit from them. As technology becomes ubiquitous in daily lives and more and more information is shared through the use of technology, the understanding of what cyberspace is and how to ensure cybersecurity become more important (Singer & Friedman, 2014). As public policy related to DOI: 10.4018/978-1-5225-1081-9.ch004

Copyright © 2017, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Old Media, New Media, and Public Engagement with Science and Technology

cybersecurity is still undergoing development, a greater level of public understanding and engagement is essential for the meaningful participation of citizens in policy debates (Berkowitz & Hahn, 2003). The dissemination of information about possible ways to protect information requires focused science communication efforts to establish pathways for a dialog between information technology experts and lay audiences. Meaningful citizen engagement in science requires ongoing and intensive efforts from organizations, scientists, and media professionals (Powell & Colin, 2008). Strategic communication and the use of mass media can provide effective ways to expose large audiences to a topic and interact with citizens to create initial connections for future engagement activities. This chapter presents an example of an event that used traditional broadcasting dissemination channels complimented by social media to facilitate a dialog between information technology experts and the general public on the topic of cybersecurity. In using this example, this chapter aims to provide a discussion of the role of science communication in public engagement with broad science and technology topics and the use of media interactivity for audience engagement with specific messages.

#askSENSEI: AN INTERACTIVE FORUM FOR CYBERSECURITY EXPERT QUESTION AND ANSWER EVENT Cybersecurity is a critical concern for citizens, industry and government. Intrusions and attacks compromise everything from our personal identities to our national security, from our ATMs to financial markets. Although the risks associated with cyber attacks are real and often devastating, it is difficult to engage the public in messages that help them stay safe. To promote public engagement on the topic of cybersecurity, the University of Florida (through a partnership between the STEM Translational Communication Research program and the College of Engineering) organized a community forum on the topic of cybersecurity. The event, Ask SENSEI, was named for the activities of the SouthEasterN Security for Enterprise and Infrastructure (SENSEI), which is engaged in basic and applied research, designs robust cyber infrastructures to counter cyber threats, and educates the public on how they can protect themselves. The community forum featured three preeminent cybersecurity scholars as panelists. The forum took place in October 2014, which was marked as a U.S. National Cybersecurity Awareness Month. Following the core topics of the National Cybersecurity Awareness Month, the forum discussed: 1. 2. 3. 4. 5.

The aspects of promoting online safety, Secure development of IT products, Internet of things, Cybersecurity for business, and Cyber crime.

Related to the five core topics, the experts who participated in the forum discussed the questions related to the threats of the Internet and cyber activity, security of personal devises, the intersection of security and household products, innovations in cybersecurity technologies, consumer safety concerns, and fraud protection. The planning for this event incorporated evaluation of the audience engagement as a core element of the forum. The event was promoted through Twitter and Facebook, and online audiences were asked

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to submit questions for the experts. Before the webinar, prospective audience members were asked to answer some demographic questions, and provide their Twitter and Facebook handles as well as a cell phone number as an identifier. The webinar was structured to cover the five cybersecurity priority topics listed previously. During the webinar audience members were asked close-ended knowledge questions. Answers to these questions could be texted as SMS messages with automated response. A live community audience was present when the webinar was recorded, providing additional opportunities for knowledge exchange between experts and the members of the public. At the end of the webinar, audience members were asked to complete a 5-question knowledge scale and provide some information about their interest in future interactive webinars that provide opportunities to communicate with experts. Subsequently, the event was edited for a traditional media source, TV viewing and broadcast as a webinar and a Public Broadcasting Service (PBS) program (“Cybersecurity,” n.d.). This event showed that involving audiences using mass media, social media, and personal outreach is challenging but important for helping the public understand the benefits and risks of developing technologies. The #askSENSEI cybersecurity forum serves as an exemplar of engaging multiple audiences on the topic of cybersecurity. This event introduced interactivity through live audience engagement in traditional broadcast format and converged possible audience engagement into the realm of social and online media. The #askSENSEI cybersecurity forum serves as an exemplar for practitioners who aim to engage multiple audiences through old and new media on the topic of cybersecurity. While we believe this format would be useful for engaging diverse audiences with other important science-related topics, the challenges of a multipronged public engagement event, including evaluation of the event results, showed that several areas warrant the discussion of theoretical and empirical literature.. First, we provide an overview of mass-medicated communication processes that contribute to audience engagement. Next, we review challenges and opportunities in measurement and evaluation of audience responses. Then, we offer a conceptualization and discuss the nature of interactivity and its connection to engagement. Finally, we conclude with the discussion of the role of science communication as the field that translates theoretical knowledge into practical application for the civic participation and public engagement with science.

MEDIA AND PUBLIC ENGAGEMENT Science Communication The use of mass media for public engagement has a long history. While social media are rapidly becoming a dominant channel of daily information and conversation exchange, (Brossard, 2013; Brossard & Scheufele, 2013), traditional broadcast media still provide opportunities to attract attention and promote engagement of large audiences (National Science Board, 2014). Traditional broadcast media can be used to raise public awareness about the opportunities and risks of technology use, and social media afford the use of interactive engagement techniques, like live commenting and audience polling. In the example of #askSENSEI, the forum ws edited for a traditional broadcast media which aired as a PBS program with the potential to reach over 500,000 households. Public engagement in science is valuable because of the potential to develop more democratic science policies as well as the opportunity to help individuals make more informed decisions. Scholars across a variety of disciplines, including communication, social psychology, and other behavioral sciences, have begun to focus their efforts on how the language used to communicate about science shapes public at-

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titudes towards the types of science we support and the behaviors we practice (Mello, Tan, Armstrong, Schwartz, & Hornik, 2013; Strekalova, 2014). For many years, science communication efforts largely emanated from a deficit model of communication wherein the goal was to simply transmit information to the public (M. C. Nisbet, 2009; M. C. Nisbet & Scheufele, 2009). Old media, such as newspapers and television, are typified by and often limited to this one-way flow of information from the source to the audience, which is in line with the deficit model. Similarly, scientists and experts who lead science outreach and engagement activities often perceive their role as deliverers of scientific content to a passive and unknowledgeable public audience (Burchell, 2007; Davies, 2008). Despite the theoretical support for the deficit model, over two decades of monitoring suggested that merely supplying individuals with scientific information is not solely effective at increasing the public’s understanding of science (Lewenstein & Brossard, 2006). Furthermore, scholars have critiqued the deficit model because it neglects to consider an individual’s specific characteristics and unique cultural context that may influence their understanding of science (Lewenstein & Brossard, 2006; Wynne, 1992, 1995). As a response to the conceptual and practical limitations of the deficit model, researchers developed the contextual framework which recognizes that an individual’s reception and understanding of a scientific message is impacted by many factors, including their existing knowledge, attitudes, and social environment (Lewenstein & Brossard, 2006; Miller, 2001; Sturgis & Allum, 2004). The contextual model implies that experts must understand their specific audience to be effective at engaging in outreach or science communication efforts. This accurate understanding of a dynamic public can be facilitated through dialogue and feedback between the scientific community and the public. Increasingly, public engagement activities and science communication efforts have incorporated space for two-way communication, such as science cafes, which spark discussion about science between scientists and the public in an informal environment (Davies, McCallie, Simonsson, Lehr, & Duensing, 2009). Concurrently, new media, such as Twitter and Facebook, are not limited to a linear transmission of information from source to audience, but instead allow users to provide immediate feedback to experts through comments and likes. These interactive features create the potential for meaningful dialogue between the scientific community and individuals, which could improve contextual knowledge between these two groups. A broad understanding of interactivity and audience engagement with new media can inform research aimed at improving civic understanding of and involvement in science.

Interactivity and Audience Engagement The Internet affords interactivity and active audience engagement with mediated messages (Ksiazek, Peer, & Lessard, 2014). However, audience engagement itself is a multi-faceted construct. Some engagement is reactionary and manifests in asynchronous user comments to messages created by content producers. These comments may come in a variety of formats, including comments posted to articles or promotional videos shared through social media channels, sharing of stories through public and private social media channels, and voting for content through likes or thumbs up/thumbs down polls. However, it may be difficult to measure the interaction effects of comments and engagement with a particular issue. More interactive audience engagement strategies allow for the audience to comment during a live event. Yet, such interaction is limited to the measurement of the audience activity during the event itself and neglects the measurement of the follow-up audience engagement with content. Combining the best features of the two methods mentioned earlier, an interactive engagement with audience allows for a

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more accurate measurement of ongoing audience engagement with content. Recognizing this as a possible area of improvement, #askSENSEI kept both SMS features and feedback survey fully functional for two weeks after the event was aired on PBS providing the audience an opportunity to interact with and comment on the content. Arguably one of the most enduring concepts in the new media landscape, interactivity was long assumed to be a buzzword that required little explication. Not surprisingly, the profusion of research that has revolved around interactivity is testimony to its enviable position in the sphere of technology innovations. Although there have been numerous definitions of interactivity (Kiousis, 2002), it is useful to place it in some historical context and equate it to early cybernetics postulations of feedback systems. Inherently, the ability to provide and receive feedback is a defining element of interactive systems. By being able to incorporate feedback in information exchanges, a sense of dialog can be realized. The ability to conduct dialog—either between a user and a technological interface or between two or more interactants using a mediated entity—is at the heart of what interactivity is all about. Modern conceptualizations of interactivity, while numerous and varied, can generally be subsumed under three different species: contingency, functionality, and user/information control. A critical analysis of these interactivity frameworks can extend research efforts aimed at evaluating the dialogue between the scientific community and the public in new media. Simultaneously, the theoretical development of the public’s understanding of science can enrich a discussion of interactivity. The contingency view assumes interactivity to be a message feature (Sundar, Kalyanaraman, & Brown, 2003). Under this consideration, interactivity refers to the degree that future messages are related (or “contingent”) on past and present messages with the key stipulation being the “threadedness” of messages. Unlike most layperson perceptions that regard two-way communication as “interactive,” the contingency notion regards such communication as “reactive” and proposes that for communication to be truly interactive, it would need to have a minimum of three threads or loops, where each thread would be contingent on the previous one. Presumably, once three loops or threads have been established, a sense of dialog can be discerned. So, for example, a message “B” would be a contextual albeit reactive response to an initial message “A.” While it is easy to think of this as an “interactive” loop, the contingency view posits that for this “reactive” thread to approach an interactive dimension, a message “C” would also need to be incorporated such that it not only accounts for the context of message “B” but also that of the initial message “A.” In contrast to the contingency view, the functional perspective treats interactivity as a feature of the medium (Sundar et al., 2003). Here, perceptions of dialog are conveyed by the presence of bells and whistles in the system. These features can include multimedia elements and structural features, and emphasize the degree to which the functionality of the interface stimulates dialog (Sundar, Bellur, Oh, Jia, & Kim, 2014). Intuitively, the functional perspective resonates with layperson perceptions (i.e., a dynamic page with a plethora of features such as pictures, audio, video elements is likely to be rated as interactive compared to a staid-looking page that merely fulfills the contingency criteria) (Kelleher, 2009). Although empirical research on interactivity has generally not accompanied theoretical progress, the existing findings shed light on its psychological import. First, audiences are generally able to discriminate between various levels of interactivity. Second, their attitudes and intentions are influenced by the degree of interactivity that is imbued in a site (and the extent to which it can be perceived by users). Traditionally, empirical propositions surrounding the psychological influence of interactivity have assumed a linear relationship between interactivity and relevant outcomes (e.g., attitudes and cognitions). That is, as the level of interactivity in a system increases, it leads to a corresponding enhancement of 61


positive attitudes (Ferber, Foltz, & Pugliese, 2005; Sundar et al., 2003). Not surprisingly, as features of digital media proliferated, website developers and analysts assigned interactivity a premium spot on the technological firmament. This excitement was also accompanied by the perception that the presence of interactivity (or interactive features) was agnostic of content—any information or content domain would benefit with the inculcation of interactivity. These beliefs resulted in interactivity being a staple of new models of consumer marketplaces (e.g., e-commerce and public governance sites) (Kalyanaraman & Sundar, 2008), but, also tellingly, offering an exciting way to infuse new zest into traditional aspects of communication (e.g., political campaigns) (Ferber et al., 2005; Sundar et al., 2003). For instance, interactivity could be a valuable campaign tool in political communication as a candidate could harness its capability and reach out to large segments of the population (Koc-Michalska, Gibson, & Vedel, 2014). By creating a website with interactive features, a candidate could enhance dialog with potential voters by not only outlining her platform and policies, but also respond to various types of questions from site visitors. Interactive websites could thus be seen as a powerful new mechanism that would be reminiscent of “pressing the flesh” campaigns without its concomitant disadvantages. Presumably, the interface would serve as an inimitable catalyst for audience engagement as manifested in audience liking, willingness to seek out information, approval of a specific political position, and so on. While the benefits of interactivity were touted by all and sundry, the actual evidence that emerged from experimental investigations revealed a somewhat different story. Contrary to almost universal assumptions, the relationship between interactivity and engagement turned out to be more complex than the hypothesized linear pattern (Ksiazek et al., 2014; Lilleker et al., 2011; Oh & Sundar, 2015). Intriguingly, research studies employing operationalizations based both on contingency and functional perspectives showed the presence of an inverted-V pattern between levels of interactivity and engagement. That is, increasing levels of interactivity did not systematically engender richer engagement but rather, there appeared to be a threshold beyond which the psychological benefits declined (Saffer, Sommerfeldt, & Taylor, 2013; Sundar & Kim, 2005). So, while websites bereft of interactive elements rated poorly on engagement metrics, websites that featured an abundance (or overabundance) of interactive features also exhibited similar outcomes, leading to scholarly pronouncements of the perils of both “too little interactivity” as well as “too much interactivity.” The optimum scenario would be one that employed a judicious mix of features. This research also attempted to explain why high levels of interactivity were perceived as less beneficial with researchers identifying the cognitive costs (among others) required to use interactive features as a key impediment in the cost-benefit equation. Even as the unexpected findings attracted more interest on the various nuances of interactivity, some scholars forwarded a third perspective that was somewhat different from either the contingency or functional views. Both the contingency view and the functional perspective emphasize elements of the message or the medium as opposed to characteristics of the receiver. Similarly, the deficit model of public understanding of science disregarded the importance of the audience characteristics (Lievrouw & Livingstone, 2006). As a response to the shortcomings of the deficit model, scholars developed the contextual model which stressed the importance of the receiver’s context in influencing their reception and understanding of the message (Barry & Doherty, 2016). The interactivity-as-information control notion exhibits a similar theoretical progression as it acknowledges the importance of the message receiver, suggesting that the key organizing principle of interactivity is not message threadedness or medium functionality, but rather the degree of control that users perceive to have over the information exchange. Such control can be accorded by technological affordances and would impel meaningful dialog between the user and interface. This viewpoint implicitly acknowledges the idea that in a majority of information 62


exchanges, audiences desire to exercise a sense of agency and control. This rationale would dispel the need to account for pronouncements such as “too much interactivity.” The information-control perspective also touts the importance of non-linearity—the ability for users to engage in and with a site with freedom and in any order and sequence that they may choose. The information-control notion is also useful in addressing consumers’ information needs over time. That is, our information-seeking preferences and goals are typically dynamic as they change and vary over time. There are times when users might espouse the need for greater engagement whereas, at other junctures, their needs might reflect more static patterns. Regardless, a sense of ownership over the ability to control how users can access and use such information is invaluable in human-technology interaction. Research employing the information-control view, while admittedly nascent, has provided meaningful insights into how interactivity can enhance engagement in various venues and domains, including civic engagement in science. The range of outcomes that have been examined include user attitudes (e.g., the degree to which audiences like a site or technology incorporating interactivity), user cognitions (e.g., the degree to which audiences learn, comprehend, and/or retain information featured on sites), and user behaviors (e.g., navigation patterns, clicking behaviors, purchase patterns). These studies have also generated insights into the mechanisms governing the relationship between interactivity and outcomes by showing that attributes such as perceived credibility function as a mediator. Interactivity has crucial implications for examining audience engagement in digital arenas. Users discriminate between and among various degrees of interactivity and their ability to do so drives different components of engagement (Ferber et al., 2005). The various moderators that could illuminate our understanding of the relationship between interactive modules and their psychological impact are many and warrant sustained and systematic inquiry. Examples of such experimental milieus include varied content platforms, longitudinal platforms, audience dynamics, among others, and would provide us with a clearer and ecumenical understanding of the role of interactivity in modern media environments, such as its importance in increasing scientist’s understanding of the public and the public’s understanding of science (Wynne, 1992). As science and technology continue to advance rapidly, the ability to effectively communicate with the public about the relevance of scientific research in everyday life has been met with many challenges (Treise & Weigold, 2002). Specifically, there are reoccurring failures in the way information is framed to portray science inaccurately and unfairly continue to cloud personal judgment and decision-making at the societal and policy-making levels. Public discourse about science is often politicized by using inflammatory or misleading language to obscure public understanding and manufacture doubt on the degree of scientific consensus that exists on a particular topic (Lewandowsky, Gignac, & Vaughan, 2013; Michaels & Monforton, 2005). The increasingly decentralized news delivery system has helped facilitate the practice of skewing the reporting of study findings to bias readers (Leach, Yates, & Scanlon, 2009; Stewart, 2013). The discourse around biotechnology, nanotechnology, stem cell research, genetically modified organisms, and climate change are all examples of topics in which language is commonly manipulated to achieve political ends rather than public understanding. Whether the aim is to affect change at the individual, population, or policy-making level, public understanding of science is paramount (Akerlof, Rowan, Fitzgerald, & Cedeno, 2012; Kahan et al., 2012). Of equal important is the active engagement of the public in the dialog about science and technology. Interactive communication with media audiences can shape the language we use and, subsequently, further facilitate the public’s understanding of and engagement in science. By further refining our focus onto the communication practices used in the realm of science, scholars and practitioners can utilize existing evidence of successful audience participation efforts to develop message strategies and audi63


ence engagement events that promote awareness, perceived relevance, understandability, and credibility of scientific research.

MASS MEDIA AND AUDIENCE ENGAGEMENT Although frequently equated to an observable behavior, audience engagement encompasses a range of reactions to information (Napoli, 2011). Audience members can get engaged by getting exposed to and learning about a particular topic; they can engage through focused attention to a topic and purposive information seeking; they can also engage through seeking opportunities and participating in active communication to advocate for a position related to an issue. Common to all these behaviors in the need for a communication channel that disseminates information and, for a two-way dialog, provides a feedback opportunity. Mass media are collectively an effective mechanism for the engagement of the general public in a debate and exchange of information related to science and technological innovations (Brossard, 2013). Overall, media coverage of a science or technology issue is likely to prompt public response, and organizations interested in disseminating science and technology news are faced with the necessity to make strategic choices regarding the type of medium for their efforts. On the one hand, traditional mass media channels, like newspapers, magazines, and radio and television broadcasting are still preferred by many audience groups (National Science Board, 2014). Furthermore, these information sources provide opportunities to attract attention and facilitate engagement of large audiences. On the other hand, online information sources are becoming more and more popular among information consumers (Brossard & Scheufele, 2013). Online media channels allow audiences to be active participants of the information sharing process and are starting to dominate daily information and communication exchange. The social media landscape is changing the process of opinion leadership (M. C. Nisbet & Kotcher, 2009; M. C. Nisbet & Scheufele, 2009). In the past, personal characteristics and immediate social influence have played a significant role, but social media allow for the self-promotion and self-identification for those who aspire to become opinion leaders. These self-made opinion leaders need the support of their more immediate social group and closer circle, and they need that support to be visible through clicks, likes, shares, and following (Park, 2013). These public actions of support, in turn, amplify their reach and establish them as opinion leaders, or influencers. With this initial support, influencers continue to reach out and create an extended network of followers to solidify their status as opinion leaders in the realm of the social media. Thus, opinion leadership within social media relies on a much more active audience participation, support, and confirmation of the status of an influencer. Social media opinion leadership is different from the traditional opinion leadership and has a dual nature. On the one hand, influencers and opinion leaders need visibility of their support to confirm their status. On the other hand, the visibility of the support expressed by some audience members allows new audience members to exercise heuristics and find these opinion leaders. Yet, although anyone theoretically has the potential to become an online influencer, few do. This provides an opportunity to segment the online audience for measurement and focus attention on those who themselves reach out to large audiences and can amplify message effects. According to recent studies, 70-90% of the online audience are lurkers, who may be active consumers of content but passive participants in the process of knowledge exchange and public debate (Han, Hou, Kim, & Gustafson, 2013; Sun, Rau, & Ma, 2014). Active participation of audiences through digital 64


channels is a societally desirable behavior that could represent an open public debate and opinion-sharing on a specific issue and inform decision- and policy-makers of the public attitudes toward existing and potential regulations. A pervasive challenge to achieving active participation of diverse audiences is the digital divide, a phenomenon that describes a growing gap and disparity between those who have access to the Internet and other technological innovations and those who do not. The digital divide contributes to the disparity in terms of lower technology literacy, health literacy, and media literacy among those who do not have access as well as lower access to information resources, and lesser access to societal resources. The digital divide leads to lower levels of civic engagement and participation in public debate (E. C. Nisbet, 2006). While an active digital footprint is necessary for the modern society, this discussion of civic engagement comes full circle back to the issue of cybersecurity and information protection for those to choose to take an active position on the social media (Bertot, Jaeger, & Hansen, 2012). Furthermore, reliance on new media as the main channel of audience engagement may lead to further disenfranchisement of groups who stand to benefit most from active participation in active communication (Dalrymple, Shaw, & Brossard, 2013; M. C. Nisbet & Kotcher, 2009). Traditional media, therefore, are necessary to include larger audiences in the process of public opinion sharing and minimize disparities in participatory knowledge exchange. In response to the changing audience information behaviors, leading traditional media channels are converging and breaking the boundaries of offline and online space by offering their content both offline and online to be responsive to the preferences of their diverse audiences. Similarly, public engagement efforts could capitalize on the strength of both traditional and online media by introducing interactive programs that cross these two media spaces. Below, we discuss the nature of audiences and possible pathways for engagement provided by social media channels. We then provide an example of how the combined use of traditional and social media channels can facilitate an interactive audience outreach effort and dialog related to technology innovations. The popularity of social media has increased dramatically in the last few years due to the incidence of services such as Twitter, Facebook, YouTube, etc. Millions of users participate in communication through these social channels daily by sharing their own content and providing feedback and comments on videos, photos, and blog posts shared by others. Clicks on link, votes, likes, shares, comments and many other actions in the mediated environment can serve as indicators of engagement with the information consumed by the general public. As a result, the data associated with audience online communicative behavior is generated at a fast pace and in a variety of formats. For instance, Twitter is used by over 300 million users who publish about 500 million tweets daily (Lupton, 2014). This interactive information and communication environment sets a unique opportunity for identifying, tracking, and extracting relations between real world events, public interest topics, individual or collective sentiments, expressed beliefs, and self-reported behaviors.

Capturing Public Engagement on Social Media Media have been trying to engage audiences for nearly a century. In 1920s, radio station managers were asking their audience to comment about programming through letters. Today, Nielsen, the largest media measurement company, is asking TV viewers to fill out a paper diary or click a button to indicate what program they are viewing to provide media companies with information to make content decisions. At the same time, web 2.0 and social media have created new opportunities for collecting audience feedback. Blogs, comments, clicks, likes, and shares are all data, but these data creates new measurement challenges.

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Audience measurement literature points out the abundance of data, the lack of standardization, and the lack of industry-wide metrics (Napoli, 2011; Webster, Phalen, & Lichty, 2013). To start identifying some harmony in, “a cacophony of competing and contradictory measurement systems” (Webster et al., 2013), one could switch off the focus on the data, turn back to the audience, and make decisions about the groups of message consumers whose behavior is important and should be measured first. Two particular audience groups who were important in the past, and who are as important in the age of social media, are opinion leaders, or influencers, and loyal message and media consumers. Social media data have unique properties that are different from traditional data sources employed in data mining and knowledge extraction domains (Tang, Chang, & Liu, 2014). Although #askSENSEI was a one-time event, collection of audience engagement data included interactions through SMS, posting of questions on Twitter, and provision of feedback through a survey instrument. Combined, these channels of audience interaction exemplified many of the data collection challenges associated with the use of social media. First, social data are big. Specific individuals may not produce considerably large data, but collective use aggregates to millions of messages per day. Second, social data are linked, and, therefore, relationships between users make the inherent knowledge heavily dependent on context. Third, social data are noisy. This means that the quality of data varies from user to user, typos and spacing errors are frequent, and not all information shared by social media users is trustworthy. Fourth, social media data are highly unstructured as it allows the creation and upload of freestyle text messages in different formats. Fifth, social data are incomplete. While many social media users provide personal information, only few, for privacy concerns, make their personal data fully available. Moreover, social media data are multimodal (Maynard, Dupplaw, & Hare, 2013) as messages may come in a variety of forms including videos, images, audio files that are shared alone or as a complement to other textual messages. Finally, social media data incorporate metadata that enriches the context of text such as geo-location, timestamps, user language preferences, or the type of device used to send a message. Despite the complexities of handling social media data, available information can be used to answer questions about social dynamics such as spatio-temporal patterns of news spread, information propagation, and audience engagement. Furthermore, knowledge extracted from social media data can give ground to a number of applications ranging from public debate and opinion tracking to the predictions of an innovation uptake and widespread use (Lupton, 2014; Park, 2013). As mentioned above, one of the methods of audience interaction that was used in #askSENSEI was collection of audience questions through Twitter, which required. collecting the data from social media, or social media mining. As defined by Zafarani et al., social media mining “is the process of representing, analyzing, and extracting meaningful patterns from data in social media, resulting from social interactions. It is an interdisciplinary field encompassing techniques from computer science, data mining, machine learning, social network analysis, network science, sociology, ethnography, statistics, optimization, and mathematics” (Zafarani, Abbasi, & Liu, 2014, p. 3). Hence, social media mining is a set of tools that enable automated, computational extraction of knowledge found in virtual social spaces and further analysis of this knowledge can be used to discover patterns in domains such as information diffusion and social behavior. Social media users frequently focus their social media communication activities to target and respond to specific interest topics that map to a variety of real life events (Weng & Lee, 2011). Consequently, event detection is one of the main purposes of social media mining. Events can be defined as a classification of a space-time region, experienced by a large number of people, which motivates its massive discussion 66


and updates on social media. Several approaches to event detection on social media, especially Twitter, have been studied in relation to their real-time nature. For instance, Sakaki et al. (Sakaki, Okazaki, & Matsuo, 2010) propose a rapid earthquake reporting system based on tweet monitoring. Their system uses textual features such as keywords in a tweet, the number of words, and their context to construct a probabilistic spatiotemporal model that considers users as geo-located sensors that report information about the targeted event. Other research has also focused on abnormal topic detection and event examination (Chae et al., 2012). This approach ranks major topics using textual analysis and discards seasonal-trend topics considering them not abnormal to construct an interactive visualization environment. This approach highlights the difference between event types that they categorized as abrupt and planned events. Other methodology of event detection in social media takes advantage of its multimodality and uses images to help categorize events extracted from social media text (Alqhtani, Luo, & Regan, 2015). It is common that event detection and identification of audience sentiment through the use of social media occurs faster that through the use and tracking of any other traditional media. Social media mining includes other methods that go beyond event identification. For example, the goal of social media mining could be knowledge extraction about audiences’ emotions, experiences, and sentiment toward consumed information. These approaches frequently included qualitative analyses of social media postings to create a comprehensive list of topics brought up by the audience to form a situational knowledge taxonomy. The taxonomy can then be used to automatically classify future messages and detect most frequently mentioned issues. For example, social media could be mined to identify topics of science communication debates and evaluate the framing of news messages (Groshek & Al-Rawi, 2013; Runge et al., 2013) or classify the information about cyber-attacks to inform most appropriate and effective response actions (Choo, 2011; Singer & Friedman, 2014).

FUTURE RESEARCH DIRECTIONS New media, whether social media or virtual reality, provides opportunities for new ways of citizen engagement, pathways for meaningful engagement still remain to be identified. Three areas stand most prominently as opportunities for future research. First, new media facilitates the collection of sociographic information about audiences. This information goes beyond traditional demographic characteristics and can include a wide range of interests, information behaviors, and communication preferences. Although these data are large and highly unstructured, identifying models and frameworks for its use in different contexts can allow scientists and policy-makes connecting with a diverse citizen base. Second, new media provides high visibility to opinion leaders. It also provides visibility to those who choose to participate in an active online dialog, e.g., through commenting. Yet, most of the online audiences remain passive consumers of information. Understanding the motivations of those who choose active engagement with online information could inform the engagement efforts that target passive audiences and prevent possible biases when voices of those who are most active are viewed as representative of the general public. Finally, the volume of information delivered to consumers through new media continues to grow, and methods of information delivery become more and more interactive. Instant tweeting, 360-degree videos, and augmented reality stories, are no longer science fiction, but the reality of science communication. However, the research on the effects of interactivity on the engagement with science and technology information is necessary to inform future public participation efforts.

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CONCLUSION Citizen engagement in science and technology requires strategic communication effort and use of multiple channels and activities to create meaningful engagement. While intensive, face-to-face communication maybe necessary for the engagement of citizens in policy debates, mass media channels can be used as lower-cost options to create opportunities for the public to participate in a dialog with scientists. The forum on cybersecurity discussed in the chapter provided an example of live audience participation supported by traditional broadcasting in combination with social media participation. Together, these methods of audience engagement provide behavioral examples, facilitate greater participation of the public in science and technology knowledge exchange, and build capacity for subsequent citizen engagement efforts.

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KEY TERMS AND DEFINITIONS Cybersecurity: A set of efforts to protect information systems from theft and unauthorized access to data and services the systems provide. Interactivity: A feature of communication and information exchange that includes contingency of future messages based on past and present messages, functionally dynamic process of communication, and/or ability of information consumers to control the flow of information by engaging with it. Mass Media: A diversified collection of media technologies that reach large audiences via print and broadcast (radio and television) channels. Public Broadcasting Service (PBS): A U.S. non-profit broadcaster and provider of public television programs. PBS provides programming in fine arts, science, history, music, public affairs and interviews and is consistently ranked the most-trusted national institution in the U.S. Science Communication: Strategic communication efforts that aim to present science and technology topics to the general public with the goal of addressing misinformation, informing decision-making, or encouraging public debate. Social Media: Technology-mediated channels that allow individuals and companies create and share media content through evolving virtual communities and networks. Social Media Mining: The process of extracting and analyzing social media interactions to recognize meaningful patterns in individual and social behavior.

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