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Public Relations Education
Association for Education in Journalism and Mass Communication
Journal of
JPRE
Volume 4, Issue ...
Volume 4, Issue 2, Fall 2018
A publication of the Public Relations Division of AEJMC
ISSN 2573-1742
© Copyright 2018 AEJMC...
Table of Contents 
Research Articles
1-20				
		
21-50 What do Employers Want? What Should Faculty Teach? A
Content Analys...
Teaching Briefs (continued)
PRD GIFT Winners from AEJMC 2018									
107-114 Teaching Trolling: Management and Strategy
L...
Journal of Public Relations Education
2018, Vol. 4, No. 2, 51-86
Teaching Digital and
Social Media Analytics:
Exploring Be...
52 		
attempted to make these connections stronger within the discipline,
yet with social media changing so quickly, profe...
Vol. 4(2), 2018	 Journal of Public Relations Education	 53
appropriate for the communications professions in which they
wo...
54 		
Commission on Public Relations Education (Toth & Lewton, 2018),
both educators and practitioners identified “researc...
Vol. 4(2), 2018	 Journal of Public Relations Education	 55
2017). Other researchers have focused on practicing social medi...
56 		
	
Although many skills related to social media have been referenced
in previous literature, there is a lack of resea...
Vol. 4(2), 2018	 Journal of Public Relations Education	 57
should also include identifying the metrics that can be used fo...
58 		
in measuring the impact of their work. The interactive website tool guides
professionals through the process of “ali...
Vol. 4(2), 2018	 Journal of Public Relations Education	 59
External Training and Certification Opportunities	
For students...
60 		
Incorporating Professional Expertise	
In addition to online training programs with analytics tools,
professors can r...
Vol. 4(2), 2018	 Journal of Public Relations Education	 61
the class, days dedicated to teaching analytics, and integratio...
62 		
case studies (α = .89); guest lectures by professionals (α = .86); the use of
professional certifications as course ...
Vol. 4(2), 2018	 Journal of Public Relations Education	 63
about digital analytic concepts both public relations students ...
64 		Ewing et al.
tweeted, “Digital PR produces a lot of data, the challenge is to turn this
data into actionable insights...
Vol. 4(2), 2018	 Journal of Public Relations Education	 65
	
Understanding context. Contextualizing data (n = 10 tweets)
a...
66 		Ewing et al.
stay up-to-date with the latest digital platforms and tools, and the student’s
ability to then choose an...
Vol. 4(2), 2018	 Journal of Public Relations Education	 67
and findings to the client. They used Excel and created a custo...
68 		Ewing et al.			
teach digital and social media analytics. Many outcomes stated on the
syllabi contained more generic ...
Vol. 4(2), 2018	 Journal of Public Relations Education	 69
their expertise. 	
Also related to RQ5, the Twitter chat partic...
70 		Ewing et al.
Discussion and Conclusion	
Incorporating digital and social media analytic training is a crucial
compone...
Vol. 4(2), 2018	 Journal of Public Relations Education	 71
through these courses. The Twitter discussion among educators a...
72 		Ewing et al.
that they either taught a digital analytics course or included digital
analytic concepts in existing cou...
Vol. 4(2), 2018	 Journal of Public Relations Education	 73
Title Times
mentioned
Likeable Social Media, Revised and Expand...
74 		Ewing et al.
public relations programs). In addition to books, many syllabi included
references to required online ar...
Vol. 4(2), 2018	 Journal of Public Relations Education	 75
Participants are unlikely to tweet the same theme to minimize r...
76 		Ewing et al.
of each course’s content to be explored. In addition, in-depth interviews
with practitioners who are exp...
Vol. 4(2), 2018	 Journal of Public Relations Education	 77
real time: Creating a social crisis simulator for the classroom...
78 		Ewing et al.
journals from 1981 to 2014. Public Relations Review, 41, 153-169.
Edministon, D. (2014). A personal comp...
Vol. 4(2), 2018	 Journal of Public Relations Education	 79
[Tweet]. Retrieved from https://twitter.com/hfsisco/
status/723...
80 		Ewing et al.
Research Project. Retrieved from http://digital-activism.
org/2013/05/picking-the-best-intercoder-reliab...
Vol. 4(2), 2018	 Journal of Public Relations Education	 81
Journal of Marketing Education, 33, 183-192. https://doi.
org/1...
82 		
visualize results, derive insights #PRAnalytics. [Tweet]. Retrieved
from https://twitter.com/bernhardmx/status/72331...
Vol. 4(2), 2018	 Journal of Public Relations Education	 83
counterintuitive, but writing & visual comm. Again, if you
can’...
84 		
EMV. Retrieved from http://wadds.co.uk/2017/06/28/ave-mutates-
emv/
Waters, R. D., & Bortree, D. S. (2011, Spring). ...
Vol. 4(2), 2018	 Journal of Public Relations Education	 85
University Name Course Names
Biola University •	 Social Media, ...
86 		
Editorial Record: Original draft submitted to JPRE March 30, 2017. Revision went
under review August 7, 2017. Manusc...
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Ewing, Kim, Kinsky, Moore, & Freberg (2018) Teaching Digital and Social Media Analytics: Exploring Best Practices and Future Implications for Public Relations Pedagogy, Journal of Public Relations Education, Volume 4, Issue 2

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Teaching Digital and
Social Media Analytics:
Exploring Best Practices and Future
Implications for Public Relations Pedagogy
ABSTRACT
One of the growing areas within public relations is digital and social
media analytics. Teaching the use of analytics to communication
students is not new, but studying what is being taught is almost
non-existent. The public relations research literature has supported
exploring the value of data analysis to gain audience insights, to
measure communication strategies, and to evaluate campaign
efforts. The purpose of this study is to explore the ways in which
faculty are teaching social media analytics. Two content analyses
were conducted to explore trends of digital and social media
analytics training. Authors analyzed related course syllabi and a
Twitter chat on the subject sponsored by the AEJMC PR Division
and PRSA Educators Academy. Findings and future implications
in teaching digital and social media analytics for educators and
public relations practitioners are discussed.

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Ewing, Kim, Kinsky, Moore, & Freberg (2018) Teaching Digital and Social Media Analytics: Exploring Best Practices and Future Implications for Public Relations Pedagogy, Journal of Public Relations Education, Volume 4, Issue 2

  1. 1. Public Relations Education Association for Education in Journalism and Mass Communication Journal of JPRE Volume 4, Issue 2, Fall 2018 A publication of the Public Relations Division of AEJMC ISSN 2573-1742
  2. 2. Volume 4, Issue 2, Fall 2018 A publication of the Public Relations Division of AEJMC ISSN 2573-1742 © Copyright 2018 AEJMC Public Relations Division   Journal of Public Relations Education Editorial Staff Emily S. Kinsky, West Texas A&M University, editor-in-chief Tiffany Gallicano, University of North Carolina at Charlotte, senior associate editor Lucinda Austin, University of North Carolina at Chapel Hill, associate editor Chuck Lubbers, University of South Dakota, associate editor of reviews Kathleen Stansberry, Elon University, web manager Note from the Editor-in-Chief: In this issue, you will find three research articles, all five of the top AEJMC PR Division’s Great Ideas For Teaching presented in Washington, D.C., and two reviews by Matt Kushin, which relate to one another on the topic of teaching social media. Volume 4, Issue 2 reflects an incredible amount of work done prior to my editorship. The previous editor-in-chief, Chuck Lubbers, handled the review assignments for each of the research articles for this issue prior to me moving into this role on Jan. 1, 2018, and two of them were accepted for publication under his tenure in 2017. The first acceptance letter I was honored to send as the editor went to Drs. Brunner, Zarkin and Yates. A special thanks to Chuck for his work with authors and reviewers to get us ready for Volume 4. Thank you to Tiffany, Lucinda, Chuck and Katie, who have invested countless unpaid hours proofreading, editing and formatting this issue. Without your service, this issue would not exist. Special thanks go to Rebekah Grome, who also came to our aid with proofreading.
  3. 3. Table of Contents  Research Articles 1-20 21-50 What do Employers Want? What Should Faculty Teach? A Content Analysis of Entry-Level Employment Ads in Public Relations Brigitta R. Brunner, Kim Zarkin, & Bradford L. Yates 51-86 Teaching Digital and Social Media Analytics: Exploring Best Teaching Briefs PRD GIFT Winners from AEJMC 2018 87-98 Building a Social Learning Flock: Using Twitter Chats to Enhance Experiential Learning Across Universities Amanda J. Weed, Karen Freberg, Emily S. Kinsky, & Amber L. Hutchins 99-106 Diagnosing Health Campaigns: A Campaign Evaluation Assignment Laura E. Willis
  4. 4. Teaching Briefs (continued) PRD GIFT Winners from AEJMC 2018 107-114 Teaching Trolling: Management and Strategy Leslie Rasmussen 115-122 Sparking Creativity Through Purpose-Driven Storytelling Chris Cooney 123-127 Looking in to see out: An Introspective Approach to Teaching Ethics in PR Regina Luttrell & Jamie Ward Reviews 128-133 Social Media Campaigns: Strategies for Public Relations and Marketing Matthew J. Kushin 134-145 Meltwater Media Intelligence Software Matthew J. Kushin
  5. 5. Journal of Public Relations Education 2018, Vol. 4, No. 2, 51-86 Teaching Digital and Social Media Analytics: Exploring Best Practices and Future Implications for Public Relations Pedagogy Michele E. Ewing, Kent State University Carolyn Mae Kim, Biola University Emily S. Kinsky, West Texas A&M University Stefanie Moore, Kent State University Karen Freberg, University of Louisville Abstract One of the growing areas within public relations is digital and social media analytics. Teaching the use of analytics to communication students is not new, but studying what is being taught is almost non-existent.The public relations research literature has supported exploring the value of data analysis to gain audience insights, to measure communication strategies, and to evaluate campaign efforts. The purpose of this study is to explore the ways in which faculty are teaching social media analytics. Two content analyses were conducted to explore trends of digital and social media analytics training. Authors analyzed related course syllabi and a Twitter chat on the subject sponsored by the AEJMC PR Division and PRSA Educators Academy. Findings and future implications in teaching digital and social media analytics for educators and public relations practitioners are discussed. Keywords: social media; social media analytics; public relations education; digital analytics The field of public relations, like many other professional disciplines, has been compelled to respond to the growing demands and shifts in the digital social landscape. Within the public relations education sector, there has been a rise of social media research (Duhé, 2015). One of the challenges in social media research and practice is to determine how to effectively bridge the expectations of practitioners with what is being taught in the classroom. Several pedagogical studies looking at social media (e.g., Kim & Freberg, 2016; Zhang & Freberg, 2018) have
  6. 6. 52 attempted to make these connections stronger within the discipline, yet with social media changing so quickly, professors face significant challenges keeping up with the trends, as well as addressing the key areas and skills students need to be successful in the field. Teaching the use of analytics to communication students is not new, but studies examining what is being taught in this area are almost non-existent; thus, an investigation of current curriculum trends related to digital analytics is a goal of the current study. Literature supports the value of data analysis to gain audience insights and shape and measure communication strategies (DiStaso, McCorkindale, & Wright, 2011; Elkin, 2017; Grates, 2016; Jain, 2016). Kent, Carr, Husted, and Pop (2011) pointed to the benefit of advances in technology to students: “With new tools like analytics in the hands of communication professionals, understanding stakeholders and publics becomes easier, and students become stronger professionals” (p. 543). As Stansberry (2016d) explains, the usefulness of social media goes far beyond sending messages; social media allow practitioners to better understand their target publics. Thus, a key skill students need to learn is how to make sense of the data available. According to Elkin (2017), the majority of marketers (72%) value employees’ data analysis abilities even more than other social media skills (65%). Beyond that, of the 12 “professional values and competencies” listed by the Accrediting Council on Education in Journalism and Mass Communications, five closely connect to the idea of teaching digital analytics. The ACEJMC (2013) guidelines have the following requirements: irrespective of their particular specialization, all graduates should be aware of certain core values and competencies and be able to . . . understand concepts and apply theories in the use and presentation of images and information . . . think critically, creatively and independently; conduct research and evaluate information by methods appropriate to the communications professions in which they work; . . . apply basic numerical and statistical concepts; apply current tools and technologies Ewing et al.
  7. 7. Vol. 4(2), 2018 Journal of Public Relations Education 53 appropriate for the communications professions in which they work, and to understand the digital world. (para. 9) The importance of instruction in analytics at all levels was emphasized by Kent et al. (2011), who said introductory students should be presented with the ideas and tools connected to analytics, while actual data gathering should be done regularly by advanced students. The authors pointed toward the ability to understand data and how to communicate the insights clearly and correctly because numbers, by themselves, do not tell the story. According to Kent et al., students need actual data to learn from so they do not rely on “stereotypes and guesses” in their campaigns; “having data allows professionals to make better decisions. Just as many professors use scenarios and case studies to teach ethics, having access to real data and helping students learn how to interpret data is valuable” (p. 541). Teaching data analytics to students in public relations is important because of what can be learned about relevant stakeholders and the environment in which an organization exists. The purpose of this study is to examine how U.S. public relations professors are teaching digital and social media analytics. Following further examination of literature in the next section, the current study will fill some of these gaps through new research efforts into what is currently taught on the topic of digital analytics and what some experts say should be taught. Literature Review Much of the research related to digital training in public relations classrooms focuses on the use of social media (Childers & Levenshus, 2016; Fraustino, Briones, & Janoske, 2015; Kim & Freberg, 2016); however, gaps remain in scholarship that specifically focus on the area of teaching social media analytics. This is an important gap to address, as the use of measurement and the ability to understand data analytics is crucial to future public relations professionals. In the 2017 report on undergraduate education from the
  8. 8. 54 Commission on Public Relations Education (Toth & Lewton, 2018), both educators and practitioners identified “research and analytics” as a highly desired skill (p. 87). The desirability of that skill was rated 4.30 by educators and 4.08 by practitioners (1 = not desired, 5 = highly desired). The educators participating in the survey also rated how well “research and analytics” is covered in their programs (m = 3.78), and practitioner participants rated how frequently that skill is found in new graduates hired by them (m = 2.70). Additionally, when asked to rate specific topics of importance for PR curriculum, both practitioners and educators rated analytics highly. On a scale of 1 (not essential) to 5 (essential), educators rated the importance of “data analytics” in the curriculum at an average of 4.15, and practitioners rated the topic 3.93 (p. 89). The topic of “measurement and evaluation” was also rated highly by educators (m = 4.57) and by practitioners (m = 4.42), as well as the topic of “social media” (m = 4.60 by educators; m = 4.46 by practitioners) (p. 89). Social Media Pedagogy Research: Concepts and Skills Early on, Anderson and Swenson (2008) studied what public relations educators should cover in class related to “new media” (p. 109). They solicited advice from PR professionals about what they should teach to best prepare their students, and one of the emerging themes was measurement. The authors followed up this research effort with a study about digital competencies (Anderson & Swenson, 2013), which also sought advice from PR professionals, specifically via a Twitter chat (#PR20Chat) and a survey of top bloggers, including Brian Solis, Arik Hanson, Gini Dietrich and Deirdre Breakenridge. Prior to the current study, the examination of social media curriculum has been rather broad; no one has yet focused specifically on teaching digital analytics in public relations. In order to best prepare students for the professional world, researchers have examined the use of social media in the industry (e.g., McCorkindale, 2010; Sundstrom & Levenshus, 2016; Wright & Hinson, Ewing et al.
  9. 9. Vol. 4(2), 2018 Journal of Public Relations Education 55 2017). Other researchers have focused on practicing social media skills in the classroom (e.g., Fraustino, Briones, & Janoske, 2015; Kinsky & Bruce, 2016; Kinsky, Freberg, Kim, Kushin, & Ward, 2016; Kinsky, Kuttis, Nutting, & Freberg, 2016; Tatone, Gallicano, & Tefertiller, 2017), including the use of multiple platforms (e.g., Janoske, Briones, & Fraustino, 2016). Researchers have also studied the use of new media by students to communicate with professors outside of the classroom (Waters & Bortree, 2011). Several studies have focused on the use of particular social media tools. Most of the research about the use of social media in the classroom has focused on Twitter (Anderson & Swenson, 2013; Carpenter & Krutka, 2014; DeGroot, Young, & VanSlette, 2015; Forgie, Duff, & Ross, 2013; Fraustino et al., 2015) and Facebook (Frisby, Kaufmann, & Beck, 2016). Facebook and Twitter have been the most frequent social media platforms utilized for public relations classroom exercises; however, LinkedIn (Edministon, 2014; Peterson & Dover, 2014), YouTube (Madden, Briones Winkler, Fraustino, & Janoske, 2016), and blogs (e.g., Moody, 2010) have also been used in communication courses. Although much of the extant research examines one platform at a time, some professors have shared their use of multiple social media platforms within their campaign client projects (Childers & Levenshus, 2016; Melton & Hicks, 2011) to teach students in public relations classes about the fundamentals of writing, campaign strategy, and research approaches. Some researchers, such as Anderson and Swenson (2013), have suggested training students to use social media professionally by using role-playing exercises and case studies, as well as using social media platforms in class. Providing assignments that create a realistic experience allows students, who will become future professionals, the opportunity to apply what they have learned in the classroom setting (Anderson, Swenson, & Kinsella, 2013). Similarly, Neill and Schauster (2015) recommended integrating math practice related to social media analytics into public relations budgeting projects in capstone courses to help students prepare for professional demands.
  10. 10. 56 Although many skills related to social media have been referenced in previous literature, there is a lack of research exclusively focused on what professionals and educators see as needed concepts and skills in the curriculum related to analytics. This lack leads to the first research question: RQ1: What digital analytic concepts and skills do both public relations students and practitioners need to understand? Digital Analytics Outcomes Certain research has focused on particular outcomes rather than platforms, one of which is analyzing target publics. According to Stansberry (2016d), “The information shared by key publics on social media sites has been a goldmine for public relations practitioners looking to understand the concerns, needs, and preferences of their target audiences” (p. 76). The public nature of so many social media platforms gives students access to an enormous amount of data for free. Stansberry (2016d) argued “teaching students to perform publics research not only exposes them to advanced social media analytics tools and techniques, it helps prepare them to thrive in a rapidly changing profession” (p. 88). This training allows students to analyze data while also brainstorming creative ways to apply their findings into campaigns, strategic plans, and situational analyses for clients and brand audits, to name a few possibilities. Social media provide practitioners with valuable data, but they are not the only digital sources that should be analyzed. Website traffic is also important to consider. Kent et al. (2011) expressed that website analysis is an important addition to social media monitoring in order to gain information “about the full range of organizational visitors” (p. 542). Moody and Bates (2013) also looked at website-related content in their study of students’ knowledge of search engine optimization and of current trends in SEO within the PR industry. Digital analytics training must not just cover collecting data, but Ewing et al.
  11. 11. Vol. 4(2), 2018 Journal of Public Relations Education 57 should also include identifying the metrics that can be used for evaluation and measurement purposes for public relations professionals and researchers. Kent et al. (2011) recommended testing students on analytic terms (e.g., bounce rate), using case studies to explain how analytics can be used in public relations, and providing real datasets for students to analyze and use to propose strategic communication changes for an organization based on the analytic results gathered. There are still some measurement concerns and issues pertaining to social media. Waddington (2017) discussed how some of the issues that occurred in traditional PR measurements are translating into the same challenges for social media. This concern about what to measure points to the importance of understanding how to analyze and interpret the data collected on social media into actionable strategies. Kent et al. (2011) recognized the different training opportunities between introductory public relations classes and advanced courses. Beginning students might simply be shown what data looks like, while upper-level courses should involve more advanced tasks such as monitoring website traffic. According to Kent et al. (2011), students can engage in more advanced work after understanding terms and concepts: The next move is to be able to understand how one variable influences another (“bounce rate and time on site are related . . .”). The third move is to be able to explain how variables change and interact over time or because of external forces (“the outbreak of Malaria drove up TOS during the month of April and also drove down the bounce rate . . .”). This sort of sequential, cause and effect, reasoning takes some time and practice to master. (p. 543) In addition, some digital analytics strategies taught in classes do not tie directly into how they impact business or communication objectives. Thus, integrating the principles and framework of social media measurement protocols from AMEC (International Association for the Measurement and Evaluation of Communication) and digital analytics frameworks and connections to DAA (Digital Analytics Association) is necessary. AMEC’s Integrated Framework (2016) helps guide communications professionals
  12. 12. 58 in measuring the impact of their work. The interactive website tool guides professionals through the process of “aligning objectives to establishing a plan, setting targets and then measuring the outputs, outtakes and outcomes” (para. 4). The Digital Analytics Association Competency Framework (2015) serves as an industry reference for employers and educators by providing an overview of the necessary knowledge, skills and competencies needed for careers in digital analytics. Most of the research exploring digital analytics courses and curriculum do not emphasize these two associations’ frameworks, which raises a point of concern. Without this bridge, there is a divide between what is being taught in the classroom and what is being implemented in practice. A first step in filling missing gaps in the curriculum is to find out what is currently expected of students in courses that include analytics training. This leads to the following research question about what students are expected to accomplish by the end of a course related to digital analytics: RQ2: What outcomes related to analytics do faculty incorporate into syllabi as part of their courses teaching analytics? Social Media Course Communication Methods Instructional methods in public relations classes have been examined by many previous researchers, and the discussion of creating a class hashtag goes back to at least 2011 (Lowe & Laffey). However, no previous studies were found that examined the inclusion of class hashtags or Facebook groups across social-media-related public relations classes. This use of particular social media communication methods within analytics-related classes leads to this study’s third research question: RQ3: What social media communication methods are embedded into courses that teach social media analytics? Ewing et al.
  13. 13. Vol. 4(2), 2018 Journal of Public Relations Education 59 External Training and Certification Opportunities For students to be prepared to process their future employers’ data, they must be trained. Like previous researchers, Stansberry (2016d) pointed out the necessity of adding new training modules to classes so that public relations students can keep up with industry: “The percentage of individuals who used social media to share multimedia content has risen rapidly, and it has become imperative that future public relations professionals be equipped with the skills to research and measure this popular form of communication” (p. 76). According to Fraustino et al. (2015), “young practitioners increasingly must develop social media skills to be competitive on the job market and successful in the workplace, and such training can start in the PR classroom” (p. 1). A number of companies have begun to offer training programs online (e.g., Hootsuite Academy, HubSpot), with some programs designed specifically for college classrooms (e.g., Meltwater). Public relations professors have taken advantage of analytics tools and tutorials for their students to learn from, as well as certain programs’ certification options, allowing students to prove their new knowledge and skills (e.g., Kinsky et al., 2016). The increasing availability of free analytics tools has made it easier to incorporate analytics training into the classroom. In light of research showing employer demand for students to meet today’s digital analytics challenges (Ewing, 2014; Fraustino et al., 2015; Kim & Freberg, 2016; Neill & Schauster, 2015; Stansberry, 2016d) and an increase in social media experiential learning in the classroom (Childers & Levenshus, 2016; Fraustino et al., 2015; Frisby et al., 2016; Kinsky & Bruce, 2016; Kinsky, Freberg, et al., 2016; Kinsky, Kuttis, et al., 2016; Madden et al., 2016), this study will also seek to explore the ways in which faculty are teaching social media analytics by integrating analytics- related certification testing: RQ4: In what ways do faculty incorporate external certifications as part of their courses teaching analytics?
  14. 14. 60 Incorporating Professional Expertise In addition to online training programs with analytics tools, professors can recruit public relations professionals with data analysis experience to speak to their classes, whether they are present in the room or joining the class via video chat technology such as Skype. Research has found value in guest speakers sharing experiences from their work (e.g., Riebe, Sibson, Roepen, & Meakins, 2013), which prompts the study’s final question about inviting external professionals as guest speakers related to analytics: RQ5: How are faculty utilizing professional experts to enhance their courses that teach analytics? Methods Phase 1: Course Syllabi To understand the ways in which professors teach social media analytics within a classroom, the authors conducted two content analyses. The first was a content analysis of course syllabi (N = 31) from faculty who teach social media analytics to communication, public relations, journalism, business, or advertising students. The syllabi were gathered from universities around the country through requests on the listservs of the Public Relations Division of the Association for Education in Journalism and Mass Communication (AEJMC) and the Educators Academy of the Public Relations Society of America. These syllabi were gathered by May 2016 and represented both undergraduate and graduate courses. Coding Procedure for Syllabi The authors coded the information from the course syllabi using 32 factors, including names of the courses, types of assignments, tools used in Ewing et al.
  15. 15. Vol. 4(2), 2018 Journal of Public Relations Education 61 the class, days dedicated to teaching analytics, and integration of industry professionals within the course. A variety of institutions were represented within the sample, including private and public, large and small, as well as universities from various areas of the U.S. (see Appendix). Intercoder Reliability for Syllabi The codebook and coding procedure were tested by the authors who independently coded each of the syllabi, randomly assigning specific ones to each author. After the initial coding, the authors examined the results, which revealed inconsistencies across multiple coding categories. To address this, the authors adjusted the codebook to provide more clear definitions for manifest syllabus content versus latent content. After the revisions, two of the authors independently coded each syllabus. Despite the initial revisions to the codebook, finding an appropriate way to evaluate the agreement between coders remained challenging due to the non-standardized structure of the syllabi and general topics listed. For example, exams and extra readings were prevalent, but whether they related specifically to analytics (one of the coding items) was not always clear. Another example of coding challenges was found in coding “course outcomes.” Some syllabi listed “objectives,” others listed “goals,” others mentioned “outcomes,” and some had none of the above. As a result, the researchers used Krippendorff’s Alpha for this study’s inter-coder reliability analysis because it is an appropriate approach when having a number of observers or levels of measurement applied in content analysis (Hayes & Krippendorff, 2007). In addition, this measurement equation looks at “observed and expected disagreement” (Joyce, 2013, para 2). After the revision of the codebook, the values for agreement among coders for these courses were as follows: courses that employ analytics within the title (α = .93); requiring textbooks (α = .67); requiring additional readings (α = .69); case studies to read (α = .69); students conducting a case study during the course (α = 1); professionals presenting
  16. 16. 62 case studies (α = .89); guest lectures by professionals (α = .86); the use of professional certifications as course requirements (α = .85); listing “KPIs” as a course outcome (α = .89); listing specific tools in course outcomes (α = .77); listing “listening” as a course outcome (α = .82); listing “insights” on the course outcomes (α = .68); listing “ethical implications” on the course outcomes (α = .72); incorporating a class hashtag (α = 1); using a class Twitter list (α = 1); and using a class Facebook group (α = 1). According to Krippendorff (2004), it “is customary to require α > .800. Where tentative conclusions are still acceptable, α > .667 is the lowest conceivable limit” (p. 241). Using these standards of measurement, the above elements each fall within the range of acceptable agreement. Phase 2: Twitter Chat The second phase of the study included a content analysis of a Twitter chat, which was held in April 2016 to allow an opportunity for crowdsourcing among public relations professionals and educators with digital analytics expertise (see Figure 1). Social media channels can be beneficial to researchers by cultivating public participation, via an open forum, where participants can respond to questions quickly (Glowacki, Lazard, Wilcox, Mackert, & Bernhardt, 2016). Similar Twitter chats have been analyzed by Anderson and Swenson (2013), Carpenter and Krutka (2014), DeGroot et al. (2015), and Fraustino et al. (2015). The chat for the current study included 56 participants and 300 tweets. Two professors and two practitioners hosted the discussion. Participants were invited through memberships in public relations academic and professional associations, as well as personal outreach to faculty networks via email and social media channels. Twitter messages were captured during an hour-long live Twitter chat, which used the hashtag #PRAnalytics. Questions were posed by the hosts, who used identifiers (e.g., Q1, Q2, Q3,) to present each question. Participants indicated which question they were responding to using identifiers (e.g., A1, A2, A3). A series of nine questions were proposed to spur discussion Ewing et al.
  17. 17. Vol. 4(2), 2018 Journal of Public Relations Education 63 about digital analytic concepts both public relations students and professionals need to understand. A thematic analysis of the tweets was conducted to determine the content that industry leaders and educators thought were best practices and to identify helpful tools for teaching digital analytics. The thematic analysis involved looking for patterns; those emerging themes became categories in the analysis for each question posed in the chat (see Fereday & Muir-Cochrane, 2006). The authors then grouped the data by category (see Riessman, 2005) to identify final concepts that emerged from the Twitter chat. Figure 1 Summary Statistics from #PRAnalytics Twitter Chat 300 tweets 54 Text Tweets 18% 116 Retweets 38.67% 68 Replies 22.67% 67 Links/Images 22.33% General Overview April 21, 2016 8:43:41 p.m. - April 22, 2016 9:56:24 a.m. 581,631 potential impacts 2,102 followers per contributor 117,686 potential reach 56 contributors 5.36 tweets per contributor Findings Concepts and Skills RQ1 explored the digital analytic concepts and skills that both public relations students and practitioners need to understand. Core themes from the Twitter chat on #PRAnalytics included measurement, contextualizing data, critical thinking skills, social listening skills, knowledge of social media and analytical tools, and digital storytelling skills. Twitter chat participants emphasized the importance of students understanding measurement (n = 12 tweets) and contextualizing data (n = 10 tweets). For example, MasterCard’s Bernard Mors (2016a)
  18. 18. 64 Ewing et al. tweeted, “Digital PR produces a lot of data, the challenge is to turn this data into actionable insights. #PRAnalytics.” PR professional Michael Brito (2016b), from LEWIS Global Communications, said, “THE most important data is audience intelligence. PR & Marketing must understand the behaviors of very specific audiences #PRAnalytics.” PR professor Kathleen Stansberry (2016a) said, “We focus too much on brand mentions/ engagement. Need to teach the importance of using data to understand audience concerns #PRAnalytics.” Measuring results. Participants in the Twitter chat advocated that public relations students should understand definitions of metrics, analysis of metrics, and use of metrics to measure strategic communication. Practitioners tended to emphasize the importance of showing business value for public relations, and one practitioner mentioned that employers are evaluating students’ understanding of digital analytics in terms of how students connect back to business objectives. Jennifer Trivelli (2016) tweeted, “The key is zeroing in on metrics that truly support biz. goals and that you can influence. That which is measured is managed. #PRAnalytics.” During the chat, professor Tim Marshall (2016) wrote, “Employers want students who connect measurement/eval back to overall biz objectives, rather than platform vanity metrics. #PRAnalytics.” Practitioners and educators also agreed on the differentiation of volume metrics and engagement metrics as one of the most important concepts for students to understand. Rather than looking at vanity metrics such as likes or retweets, these individuals recommended focusing on metrics testing engagement, while not confusing terms like volume, reach, and influence. When people directly interact with a brand through writing a comment, sharing a post and extending the reach or influencing other levels of publics that the brand could not directly reach, this type of social media activity would be considered engagement. In other words, students should understand how to specifically track and measure direct interaction with publics that can show outcomes for social media activities as opposed to simply grabbing quick data points (vanity metrics) that do not show whether the public is truly interacting on social media with the brand.
  19. 19. Vol. 4(2), 2018 Journal of Public Relations Education 65 Understanding context. Contextualizing data (n = 10 tweets) and critical thinking skills (n = 10 tweets) were recurring themes among all Twitter chat participants for questions about concepts, skills, best practices, and pitfalls students have when analyzing data. Participants emphasized the importance of understanding how to transform the data into actionable insights. Critical thinking abilities included asking questions, analyzing metrics, and operationalizing key terms. Overall, both practitioners and educators articulated the struggle with getting lost in the data and recognizing which data to mine and analyze, and then developing meaningful insights to drive communication strategies. For example, Mors (2016b) said, “Same practices 4 social & traditional PR: set objectives & KPIs, tools to capture data, visualize results, derive insights. #PRAnalytics.” PR professor Ai Zhang (2016b) posted, “Contextualize data to draw meaningful conclusions → drive strategic decision-making. #PRAnalytics.” Professor Stansberry (2016c) tweeted, “Learn to speak (and write) in the language of the C-Suite. Ask the right questions. Always be critical of your data. #PRAnalytics.” Brito (2016a) pointed out that “anyone can look at data, run a report, spew out #s. Very few can extract an insight that can drive a narrative/program. #PRAnalytics.” Using tools and listening. Social listening skills and knowledge of social media and analytical tools also emerged as valuable digital analytic skills for public relations students and graduates, with each topic generating at least eight responses. Listening skills (n = 8 tweets) focused on the ability to monitor social environments, including using listening tools. Winkler (2016a) tweeted, “Social listening is the process of monitoring digital media channels to devise a strategy that will better influence consumers. trackmaven.com #PRAnalytics.” PR professor Katie R. Place (2016) tweeted this assignment suggestion: “Basic one, but we learned so much from taking on a real client and producing monthly social listening/monitoring reports. #PRAnalytics.” Connected to both RQ1 and RQ4, knowledge of social media tools (n = 8 tweets), native analytic tools (n = 5 tweets), Google Analytics (n = 5 tweets) and Hootsuite (n = 4 tweets) encompassed a student’s ability to
  20. 20. 66 Ewing et al. stay up-to-date with the latest digital platforms and tools, and the student’s ability to then choose an appropriate platform given an organization’s goals or clients. In line with the Twitter chat, the content analysis of syllabi showed faculty use a variety of tools and resources to prepare students. Some of the popular social media tools mentioned on the syllabi were Google Analytics (n = 11), Hootsuite (n = 10), Facebook analytics (n = 6), Twitter analytics (n = 4), Storify (n = 3), Google Adwords (n = 3), Excel (n = 3), Crimson Hexagon (n = 2), Radian6 (n = 1), Canva (n = 1), Klout (n = 1) and Sprout Social (n = 1). Despite the plethora of analytic software available, some Twitter chat participants (n = 3) noted that it is not necessarily important for students to have familiarity with a wide range of tools, but it is more important for them to understand the data and methods behind specific platforms, so they have the ability to transition from platform to platform. Since analytics tools come and go, professor Itai Himelboim’s syllabus provided a valuable assignment faculty could consider. In his Listening and Engagement course (I. Himelboim, personal communication, Feb. 2, 2016), students are assigned to work in groups for the duration of the semester, and in one of the assignments, they are asked to find, learn, and generate a report based on a new social media analytic or listening tool. Students are required to find a free social media listening tool or one that offers a free trial. Students must choose the tool or tools that help them address their client’s questions/meet their goals best. Their final report is to summarize social media activity related to their client/ topic, using Crimson Hexagon, which they learn in class, as well as the free tool used to collect and analyze the data. In another analytics course evaluated in the study (S. Moore, personal communication, March 21, 2016), students worked individually and in groups to define, measure, analyze and report on a client’s website activity based on the client’s objectives. Students identified and included key performance indicators (KPIs) and a summary of their findings along with recommendations for improvement. They incorporated visualizations and graphics to best represent and accurately communicate important data
  21. 21. Vol. 4(2), 2018 Journal of Public Relations Education 67 and findings to the client. They used Excel and created a custom Google dashboard for reporting. Another project related to those found in the syllabus analysis was found in the review of literature. Stansberry (2016d) created a five- week project where her students worked in teams and used free tools (e.g., Hootsuite, Google Trends, BuzzSumo, IssueCrawler) to identify key publics and to conduct a content analysis, a social media audit, an online social network analysis and content tracking, which her students rated as valuable; they appreciated the applied, experiential lesson as something that would help distinguish them from others applying for the same job in the future. Storytelling. Another prevalent digital analytic concept identified by participants was digital storytelling, or the ability to look at data, extract insights, and then present the data in a compelling manner. When it comes to analytics, students need to integrate their critical thinking skills with their storytelling abilities to share the data in a meaningful way that connects with audiences. For example, PR professor Hilary Fussell Sisco (2016) said, “I always want . . . students to visualize data. Infographics and other visual tools to explain data makes it #munchable. #PRAnalytics.” Zhang (2016a) tweeted, “Tell digital stories. Use live videos. I am playing with @Animoto & PowerDirector. Love them very much #PRAnalytics.” While Stansberry (2016b) commented, “Seems counterintuitive, but writing & visual comm. Again, if you can’t give the data meaning, it’s pointless. #PRAnalytics.” Other concepts discussed during the Twitter chat included understanding Excel pivot tables, functions, and formulas (n = 4 tweets) and search engine optimization (n = 3 tweets). The Twitter participants commented that students shouldn’t be “afraid of math” and should learn how to use Excel to sort and analyze data. Outcomes RQ2 focused on understanding stated outcomes for courses that
  22. 22. 68 Ewing et al. teach digital and social media analytics. Many outcomes stated on the syllabi contained more generic wording with only 6% listing “KPIs” (n = 2); 35% listing specific tools (n = 11); 10% listing “insights” (n = 3); and 13% mentioning ethical implications (n = 4). The most frequently mentioned analytics tools included Google Analytics (n = 11), Hootsuite (n = 10), Facebook Insights (n = 6) and Twitter Analytics (n = 4). RQ3 focused on understanding specific social media communication methods that were used in courses. Results from the content analysis of syllabi indicated that a class hashtag was the most popular, with 26% of the syllabi incorporating this (n = 8). Based on the syllabi, it was difficult to know if hashtags were used for synchronous Twitter discussions or if they were simply used to categorize and share online resources among the class. Additional required online interactions noted on syllabi included participating in live-tweeting events, reading and/or posting to a course or professor’s blog, tagging a professor in tweets, and working to improve individual Klout scores. Only one syllabus mentioned using a Facebook group, and none mentioned a required Twitter list. RQ4 focused on what ways professors were utilizing external certifications to train students in analytics. Findings from the syllabus content analysis indicated that the majority of courses did not require students to complete an external certification that had an analytic element. The 28% that did incorporate certifications (n = 9) primarily required Hootsuite, Google Analytics, or Google AdWords. Results from the Twitter chat related to RQ4 included three participants advocating Google Analytics certification as one of the most valuable certifications in the industry. Additional online resources mentioned on syllabi to supplement classroom instruction included Code Academy, Google’s Analytics Fundamentals, Khan Academy, Lynda and the Marketing Analytics Initiative at Darden website. RQ5 focused on the ways faculty utilized outside professionals or organizations to help teach analytics. Based on the content analysis of the syllabi, 66% of courses (n = 21) relied on outside professionals to share
  23. 23. Vol. 4(2), 2018 Journal of Public Relations Education 69 their expertise. Also related to RQ5, the Twitter chat participants discussed the use of several outside resources, including the Institute for Public Relations, AEJMC, and other relevant academic or professional organizations. For example, PR pro Mors (2016c) suggested, “The @InstituteForPR has some great resources on website http://instituteforpr.org #PRAnalytics.” Twitter chat participants also mentioned outreach to professors and practitioners to serve as class speakers and/or to offer insight about teaching digital analytics. Professor Rowena Briones Winkler (2016b) said she wanted to “give a shout out to my @AEJMC_PRD friends” for being “SO helpful, re: teaching help! #soblessed #PRAnalytics.” Further, online tools such as Microsoft, Lynda, and Google Video were emphasized during the Twitter conversation. Professor Matt J. Kushin (2016) tweeted, that Microsoft has “an academic alliance program that provides many tools.” During the Twitter chat, several themes emerged for assignments focused on teaching digital analytics, such as working with an actual client, using dashboards, performing listening projects, and generating reports. Educators stressed the importance of tying these assignments to real-world clients. The responses indicated that these assignments would give students realistic application by requiring them to submit client-monitoring reports and to develop strategic-communication recommendations based on insights gleaned from the data analysis. Responses from students who participated in the Twitter discussion indicated that assignments requiring the creation of a blog and the teaching of SEO best practices helped them understand digital analytics and drive traffic on their own websites. During the Twitter chat discussion, both educators and practitioners advocated for ongoing opportunities to access, mine, and analyze data. These activities were thought to be key to creating an understanding of digital analytics in the practice of PR. Professor Jamie C. Higdon (2016) said, “Integrate analytics throughout educational journey. Require SMART objectives and metrics plan for all major projects. #PRAnalytics.”
  24. 24. 70 Ewing et al. Discussion and Conclusion Incorporating digital and social media analytic training is a crucial component of the future of social media education (Kent et al., 2011). This study examined specific pedagogical practices identified within manifest content on syllabi and in a Twitter chat among educators and practitioners in order to explore current practices and standards for analytic training. To address whether courses were meeting employers’ demand for new analytic skillsets, it made sense to begin this study by examining learning outcomes stated on syllabi. Outcomes are designed to set the tone for a course and also identify the primary goals of student learning. Therefore, looking at student learning outcomes stated on syllabi is particularly important when examining an instructor’s approach to teaching digital analytics. With the growing efforts to measure and evaluate digital activities, analytic competencies were a natural focus for social media and digital communication courses. Thus, it was expected that courses would have clearly identified learning outcomes for students related to digital analytics. However, very few courses had outcomes specifically mentioning analytics. While educators embedded analytic concepts and training within their courses, the wording of their learning outcomes did not reflect the focus on digital analytic competencies. For example, only two of the syllabi reviewed mentioned KPIs, and only three mentioned listening or insights, which are basic analytical competencies. This initial finding indicated that, while analytics are taught in these courses, classes might not be focusing on this area, resulting in the course outcomes often ignoring or only leading to inferences about course expectations in this area. With the Commission on Public Relations Education report (Toth & Lewton, 2018) identifying the value both educators and professionals place on analytics and measurement competencies, it seems important for educators to not only embed these competencies within courses but to also explicitly identify them as a learning outcome that students will be gaining
  25. 25. Vol. 4(2), 2018 Journal of Public Relations Education 71 through these courses. The Twitter discussion among educators and practitioners clearly conveyed the importance of public relations students and graduates understanding digital analytics. Based on feedback from practitioners, existing research, and analysis of syllabi, the following are recommended learning outcomes faculty might consider incorporating in their digital analytics course syllabi: 1. To identify the importance of online data in strategic planning and validating ROI. 2. To identify online influencers and the major users of various types of digital and social media. 3. To use analytics tools and technologies to capture data, generate reports and glean insights. 4. To analyze ethical implications associated with interpreting and using online data. 5. To discuss the impact of digital and social media on relationships between organizations and their stakeholders. 6. To evaluate how stakeholder engagement on social media channels affects organizational operations. 7. To articulate definitions and measurements of social media engagement and website traffic. 8. To apply basic numerical and statistical concepts to evaluate, plan, and implement strategic digital tactics. 9. To apply concepts and theories in presenting findings and in creating visualizations and dashboards to share with management/ client. 10. To become Hootsuite and/or Google Analytics certified. One of the key areas that is suggested in social media education is for faculty to help students understand professional uses of the platforms (Kim & Freberg, 2016), including analytic information (Anderson & Swenson, 2013). Recognizing this need, the current study examined the ways in which faculty incorporate professionals into the classroom. Numerous educators who participated in the Twitter discussion shared
  26. 26. 72 Ewing et al. that they either taught a digital analytics course or included digital analytic concepts in existing courses. The majority of syllabi indicated that faculty were including professionals by bringing them in for guest lectures; however, it was difficult to identify within the syllabi whether these professionals specifically addressed topics of analytics or other areas incorporated within the class such as campaign management, content creation, or platform functions. An area of growth between professional organizations and the classroom has been the opportunity for student certifications on specific platforms such as Hootsuite, Google, and HubSpot (Kinsky, Freberg, et al., 2016). While this is an increasingly popular choice to help students gain competencies, the authors were surprised to find only about a fourth of the 31 syllabi mentioned an external certification as part of the course requirements. In addition to previous literature pointing to the value of certifications (e.g., Kinsky, Freberg, et al., 2016), three Twitter participants mentioned the importance of external certification. The availability of free, high quality, external training programs offered online (e.g., Hootsuite, HubSpot, Google) makes it easier for educators to provide up-to-date, industry-relevant preparation for students, and educators should take advantage of these programs. We predict their inclusion on future syllabi will increase. Another key finding of the study is the lack of consistency in resources on the subject of digital analytics, including required textbooks and online sources. Syllabi included a wide range of industry books used to teach students about the subject (see Table 1). This is, in part, due to the content and structure of the course and whether analytics was the sole topic or if it was only a smaller component of the social media or digital curriculum. This inconsistency in required books is something that has been noted in previous studies looking at the social media curriculum (Kim & Freberg, 2016). Due to the nature of the rapid changes in the field, educators have to frequently update their sources. Textbook and resource choices are also impacted by where the class is being taught within a university (e.g., marketing programs may use different textbooks than
  27. 27. Vol. 4(2), 2018 Journal of Public Relations Education 73 Title Times mentioned Likeable Social Media, Revised and Expanded: How to Delight Your Customers 3 Measure What Matters 3 Groundswell Expanded and Revised Edition 2 Web Analytics 2.0 2 What Happens on Campus Stays on YouTube 2 AP Stylebook 1 Advertising and Public Relations Research 1 The Basic Practice of Statistics 1 Contagious 1 Cutting-Edge Marketing Analytics 1 Digital Marketing Analytics 1 Good Strategy Bad Strategy 1 How to Measure Social Media: A Step-by-Step Guide to Developing and Assessing Social Media ROI 1 How to Use Google Analytics the Tutorial 1 Maximize Your Social: A One-Step Guide to Building a Social Media Strategy for Marketing and Business Success 1 Measuring the Networked Nonprofit: Using Data to Change the World 1 Mediactive 1 The Power of Visual Storytelling 1 Predictive Analytics 1 Primer of Public Relations Research 1 ProBlogger: Secrets for Blogging Your Way to a Six-Figure Income 1 Table 1 Required Textbooks for Digital and Social Media Analytics Classes
  28. 28. 74 Ewing et al. public relations programs). In addition to books, many syllabi included references to required online articles, white papers, and PDFs, but few syllabi specified titles of these resources. For RQ3, in examining pedagogical practices to teach social media and analytics, the authors examined other social media communication methods professors had incorporated in their syllabi to facilitate online interaction. Some of the interactions mentioned involved the use of a class hashtag, Facebook groups, Twitter chats, Storify, and live tweeting. Future Research and Limitations This study explored basic questions related to pedagogical practices and teaching social media analytics. In order to provide a foundational knowledge, the authors examined the manifest content of 31 syllabi and a Twitter chat among 56 public relations practitioners and educators. One limitation of the study is that the themes identified through the Twitter chat were based on a small number of affirmative responses; however, this is typical because of the dynamics of a Twitter conversation. Title Times mentioned Real-Time Marketing & PR 1 Share This 1 The Social Current 1 Social Media Intelligence 1 Social Media Marketing 1 Social Media ROI 1 Socialnomics: How Social Media Transforms the Way We Live and Do Business 1 The Signal and the Noise 1 Your Brand, the Next Media Company: How a Social Business Strategy Enables Better Content, Smarter Marketing and Deeper Customer Relationships 1 Table 1 (continued).
  29. 29. Vol. 4(2), 2018 Journal of Public Relations Education 75 Participants are unlikely to tweet the same theme to minimize repetitive content. Another limitation to using the chat data is that people who valued the topic were more likely to participate in the Twitter chat than people who were disinterested or didn’t value it. Future studies may consider in-depth explorations through discussions with the faculty who are teaching the courses. Future studies could incorporate a mixed-method approach involving focus groups and interviews with professionals to determine if these digital analytics assignments were effective in preparing students for their new roles, perhaps following the methods of Gallicano, Ekachai, and Freberg’s (2014) study of an infographic assignment. In addition, testing the effectiveness of certification programs (e.g., Kinsky, Freberg, et al., 2016) for analytics could be beneficial as well. Educators can also integrate and test how certain assignments are implemented and accepted within digital analytics by using guidelines and frameworks accepted in digital analytics associations and professional circles. Many frameworks, like the ones proposed by AMEC and DAA, can be integrated and used in current courses for lessons and used as inspiration to create assignments for students to test their knowledge and application skills in digital analytics. Further research could explore classes that use a specific framework for assignments and those that do not, and compare the end results. In addition, interviews with digital analytics professionals who are a part of these associations could be explored in future research to determine what they feel are key areas to emphasize, growing trends, and challenges and opportunities in the field. Although course syllabi provided a general overview, often information seemed missing or vague. It does not mean faculty failed to incorporate certain pedagogical practices in their classes; their absence may indicate that they were simply not shared through the syllabus, and this could have been done with the purpose of keeping the class nimble as technology changes. Future researchers can learn from and anticipate coding challenges encountered in this foundational study. Direct conversations with professors would allow more specific details
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  34. 34. 80 Ewing et al. Research Project. Retrieved from http://digital-activism. org/2013/05/picking-the-best-intercoder-reliability-statistic-for- your-digital-activism-content-analysis/ Kent, M. L., Carr, B. J., Husted, R. A., & Pop, R. A. (2011). Learning web analytics: A tool for strategic communication. Public Relations Review, 37, 536- 543. https://doi.org/10.1016/j.pubrev.2011.09.011 Kim, C., & Freberg, K. (2016). The state of social media curriculum: A proposed framework for social media pedagogy. Journal of Public Relations Education, 2, 68-82. Kinsky, E. S., & Bruce, K. (2016). “It throws you into the ring”: Learning from live-tweeting. Teaching Journalism and Mass Communication, 6(1), 36-52. Retrieved from http://aejmc.us/wp- content/uploads/sites/9/2016/04/tjmc-w16-kinsky.pdf Kinsky, E. S., Freberg, K., Kim, C., Kushin, M., & Ward, W. (2016). Hootsuite University: Equipping academics and future PR professionals for social media success. Journal of Public Relations Education, 2(1), 1-18. Retrieved from http://aejmc.us/jpre/wp- content/uploads/sites/25/2016/02/JPRE-2-1-Full_Journal_All_ Articles.pdf#page=3 Kinsky, E. S., Kuttis, K., Nutting, B. H., & Freberg, K. (2016, October). Projecting a live Twitter stream in the communication classroom: How students engage and process information while live tweeting a lecture. Paper presented at the meeting of the Public Relations Society of America Educators Academy, Indianapolis, IN. Krippendorff, K. (2004). Content analysis: An introduction to its methodology. Thousand Oaks, CA: Sage. Kushin, M. [MJKushin]. (2016, April 21). @PRSAEducators they have an academic alliance program that provides many tools https:// www.microsoft.com/en-us/education/products/dynamics/default. aspx?Search=true … #PRAnalytics [Tweet]. Retrieved from https://twitter.com/mjkushin/status/723310276737536000 Lowe, B., & Laffey, D. (2011). Is Twitter for the birds? Using Twitter to enhance student learning in a marketing course.
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  36. 36. 82 visualize results, derive insights #PRAnalytics. [Tweet]. Retrieved from https://twitter.com/bernhardmx/status/723315002745065473 Mors, B. [bernhardmx]. (2016c, April 21). The @InstituteForPR has some great resources on website http://instituteforpr.org #PRAnalytics [Tweet]. Retrieved from https://twitter.com/bernhardmx/ status/723307510174601216 Neill, M. S., & Schauster, E. (2015). Gaps in advertising and public relations education: Perspectives of agency leaders. Journal of Advertising Education, 19(2), 5-17. https://doi. org10.1177/109804821501900203 Peterson, R. M., & Dover, H. F. (2014). Building student networks with LinkedIn: The potential for connections, internships, and jobs. Marketing Education Review, 24, 15-20. https://doi.org10.2753/ MER1052-8008240102 Place, K. R. [KatiePlace]. (2016, April 21). A5: Basic one, but we learned so much from taking on a real client and producing monthly social listening / monitoring reports. #PRanalytics [Tweet]. Retrieved from: https://twitter.com/KatiePlace/status/723309630357667840 Riebe, L., Sibson, R., Reopen, D., & Meakins, K. (2013). Impact of industry guest speakers on business students’ perceptions of employability skills development. Industry and Higher Education, 27(1), 55-66. https://doi.org/10.5367/ihe.2013.014010.5367/ ihe.2013.0140 Riessman, C. K. (2005). Narrative analysis. In N. Kelly, C. Horrocks, K. Milnes, B. Roberts, & D. Robinson (Eds.), Narrative, memory & everyday life (pp. 1-7). Huddersfield, UK: University of Huddersfield. Stansberry, K. [KStansberry]. (2016a, April 21). A1: We focus too much on brand mentions/engagement. Need to teach the importance of using data to understand audience concerns #PRAnalytics [Tweet]. Retrieved from https://twitter.com/kstansberry/ status/723302265386356737 Stansberry, K. [KStansberry]. (2016b, April 21). A2: Seems Ewing et al.
  37. 37. Vol. 4(2), 2018 Journal of Public Relations Education 83 counterintuitive, but writing & visual comm. Again, if you can’t give the data meaning, it’s pointless. #PRAnalytics [Tweet]. Retrieved from https://twitter.com/kstansberry/ status/723304378237632513 Stansberry, K. [KStansberry]. (2016c, April 21). Q9: Learn to speak (and write) in the language of the C-Suite. Ask the right questions. Always be critical of your data #PRAnalytics [Tweet]. Retrieved from https://twitter.com/kstansberry/status/723315285760040960 Stansberry, K. (2016d). Taming the social media data deluge: Using social media research methods in the public relations classroom. In H. S. Noor Al-Deen (Ed.), Social media in the classroom (pp. 75-92). New York, NY: Peter Lang. Sundstrom, B. L., & Levenshus, A. B. (2016). The art of tweeting: Integrating primary social media research into a public relations writing course. In H. S. Noor Al-Deen (Ed.), Social media in the classroom (pp. 111-130). New York, NY: Peter Lang. Tatone, J., Gallicano, T. D., & Tefertiller, A. (2017). I love tweeting in class, but… A qualitative study of student perceptions of the impact of Twitter in large lecture classes. Journal of Public Relations Education, 3(1), 1–13. Retrieved from http://aejmc.us/ jpre/2017/05/24/i-love-tweeting-in-class-but-a-qualitative-study- of-student-perceptions-of-the-impact-of-twitter-in-large-lecture- classes Trivelli, J. [TrivelliJ]. (2016, April 21). The key is zeroing in on metrics that truly support biz. goals and that you can influence. That which is measured is managed. #PRAnalytics [Tweet]. Retrieved from: https://twitter.com/trivellij/status/723316267214471168 Toth, K., & Lewton, K. (Eds). (2018). Fast forward foundations + future state: Educators + practitioners. Commission on Public Relations Education. Retrieved from http://www.commissionpred. org/commission-reports/fast-forward-foundations-future-state- educators-practitioners/ Waddington, S. (2017). New metric, same old flaws: AVE mutated into
  38. 38. 84 EMV. Retrieved from http://wadds.co.uk/2017/06/28/ave-mutates- emv/ Waters, R. D., & Bortree, D. S. (2011, Spring). Communicating with millennials: Exploring the impact of new media on out-of-class communication in public relations education. Teaching Public Relations Monograph, 80, 1-4. Retrieved from http://aejmc.us/prd/ wp-content/uploads/sites/23/2014/11/tpr80sp11.pdf Winkler, R. B. [DrRBWinkler]. (2016a, April 21). A1: I think social listening is an increasingly important concept/strategy to teach PR students http://qub.me/2_jtN0 #pranalytics [Tweet]. Retrieved from https://twitter.com/DrRBWinkler/ status/723301393658949632 Winkler, R. B. [DrRBWinkler]. (2016b, April 21). A4: Imma give a shout out to my @AEJMC_PRD friends, who I have been SO helpful, re: teaching help! #soblessed #PRAnalytics [Tweet]. Retrieved from https://twitter.com/DrRBWinkler/status/723308434746163202 Wright, D. K., & Hinson, M. D. (2017). Tracking how social media and other digital media are being used in public relations practice: A twelve-year study. Public Relations Journal, 11(1), 1-31. Retrieved from https://prjournal.instituteforpr.org/wp-content/uploads/PRJ- 2017-Wright-Hinson-2-1.pdf Zhang, A. [aiaddysonzhang]. (2016a, April 21). A2: Tell digital stories. Use live videos. I am playing with @Animoto & PowerDirector. Love them very much #PRAnalytics [Tweet]. Retrieved from https://twitter.com/aiaddysonzhang/status/723304971920400387 Zhang, A. [aiaddysonzhang]. (2016b, April 21). A7: Contextualize data to draw meaningful conclusions --> drive strategic decision making #PRAnalytics [Tweet]. Retrieved from https://twitter.com/ aiaddysonzhang/status/723313458922565632 Zhang, A., & Freberg, K. (2018). Developing a blueprint for social media pedagogy: Trials, tribulations, and best practices. Journal of Public Relations Education, 4(1), 1-24. Retrieved from http://aejmc. us/jpre/2018/05/21/developing-a-blueprint-for-social-media- pedagogy-trials-tribulations-and-best-practices/ Ewing et al.
  39. 39. Vol. 4(2), 2018 Journal of Public Relations Education 85 University Name Course Names Biola University • Social Media, SEO and Digital Strategy Carnegie Mellon University • Digital Marketing Analytics Cleveland State University • Media Metrics and Analytics Elon University • Strategies for Emerging Media University of Florida • Consumer and Audience Analytics • Introduction to Social Media • Social Media Skills University of Georgia • Public Relations Research • Social Media Analytics, Listening and Engagement • Coding for Interactive Media Iona College • Applied Communications Research Kent State University • Digital Analytics for Ad and PR • Public Relations Online Tactics Louisiana State University • Public Relations and Social Media Strategy Loyola University • Audiences and Distribution University of Maryland • New Media Writing for Public Relations Massachusetts Institute of Technology (MIT) • Digital Marketing and Social Media Analytics Appendix University Syllabi Used for Coding
  40. 40. 86 Editorial Record: Original draft submitted to JPRE March 30, 2017. Revision went under review August 7, 2017. Manuscript accepted for publication October 8, 2017. Final edits completed July 20, 2018. First published online August 17, 2018. University Name Course Names Ohio Northern University • Social Media Principles University of Oregon • Social Media Insights and Measurement • Analytics and Adwords New York University (Stern School of Business) • Coding for Interactive Media San Diego State University • Digital and Social Media Analytics University of Southern California • Data Analytics Driven Dynamic Strategy & Execution • Digital Analytics University of South Dakota • Internet Marketing and Communication Syracuse University • Social Media Theory and Practice • Using Big Data and Analytics (Maymester Course) Texas Christian University • Social Media Measurement University of Virginia • Marketing Analytics West Texas A&M University • New Media • Seminar in Media Innovations and Management Ewing et al. Appendix (continued) University Syllabi Used for Coding

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