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Sociotechnical stewardship in higher education: a field study of social media policy documents

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Sociotechnical stewardship in higher education: a field study of social media policy documents

Abstract and Figures

Social media use has risen in higher education, as campus stakeholders frequently access these technologies for teaching, learning, research, communication, and information sharing. With these connected, digital technologies, our colleges and universities understand there are both opportunities and threats that social media affords. Higher education has increasingly witnessed a number of challenging incidents and abuses online. As a result, a number of institutions are evaluating policies and practices to regulate online behavior and establish community standards for students, staff, and faculty. Using latent semantic analysis, 36 universal topics are extracted from the 250 policy documents. This study not only establishes reference database of social media policy documents representing ten countries, it also forms the ontology to develop the framework foundation of sociotechnical stewardship to support strategic, long-term technology planning for organizations and their stakeholders.
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Sociotechnical Stewardship in Higher Education: A Field Study of So-
cial Media Policy Documents
Laura A. Pasquini, Department of Learning Technologies, College of Information, University of North
Texas, Denton, USA
Nicholas Evangelopoulos, Information Technology and Decision Sciences, College of Business, Univer-
sity of North Texas, Denton, USA
Abstract
Social media use has risen in higher education, as campus stakeholders frequently access these technolo-
gies for teaching, learning, research, communication, and information sharing. With these connected, dig-
ital technologies, our colleges and universities understand there are both opportunities and threats that so-
cial media affords. Higher education has increasingly witnessed a number of challenging incidents and
abuses online. As a result, a number of institutions are evaluating policies and practices to regulate online
behavior and establish community standards for students, staff, and faculty. Using latent semantic analy-
sis, 36 universal topics are extracted from the 250 policy documents. This study not only establishes ref-
erence database of social media policy documents representing ten countries, it also forms the ontology to
develop the framework foundation of sociotechnical stewardship to support strategic, long-term technol-
ogy planning for organizations and their stakeholders.
Keywords
Sociotechnical; Stewardship; Higher education Policy; Social media; Latent semantic analysis
Cite as:
Pasquini, L. A., & Evangelopoulos, N. (2016). Sociotechnical stewardship in higher education: A field study of
social media policy documents. Journal of Computing in Higher Education, 1-22. Advance online publication. doi:
10.1007/s12528-016-9130-0 Published Online November 21, 2016.
Introduction
Social media technologies are currently transforming how our society communicates and
shares information. Social media is a classification for a wide variety of popular technologies
that are open, facilitate interactivity, and encourage connectivity. Kaplan and Haenlein (2010, p.
62) define social media as “a group of Internet-based applications that build on the ideological
and technological foundations of Web 2.0, and that allow the creation and exchange of User
Generated Content.” Social media gives individuals the ability to create, publish, and communi-
cate. The social media landscape is rich and diverse with a variety of platforms that differ in
terms of their scope and functionality, including presence, relationships, identity, groups, shar-
ing, conversations, and reputation (Kietzmann, Hermkens, McCarthy, & Silvestre, 2011). In the
broadest terms, social media spaces exist for user-generated content and social interaction online
where “everybody and anybody can share anything anywhere anytime” (Joosten, 2012, p. 14).
Although an increasing number of applications and platforms can be classified as social media,
the dominant features of these sites include organic communication, shared information, and so-
cial interactions driven by individual use.
Social media use in higher education
As digital communication becomes a fluid part of our lives, an increasing number of col-
leges and universities are connecting with students, faculty, staff, and alumni on social media.
Social technologies offer creative educational opportunities and dynamic learning environments
2
that extend the possibilities of typical education technologies, such as computer, media, and
learning management systems, offer new scenarios for social collaborations and a variety of
learner exchanges. Our higher education organizations are effectively part of a sociotechnical
system (STS) where the mutual constitution of people and digital technologies are contextually
embedded and collective action is critical (Sawyer & Jarrahi, 2013). To further explain this defi-
nition, sociotechnical is the interaction between people and technology, specifically as we con-
tinue to intertwine technical infrastructures with our social behaviors. Social media applications
are changing how Internet technology in higher education is being used (Wheeler, 2009) in our
sociotechnical organizations, specifically with regards to the distribution of course materials,
communication channels on campus, and enhancement of collaborative learning and knowledge
building (Collins & Halverson, 2010; Schroeder, Minocha, & Schneider, 2010). With the perva-
siveness of mobile computing devices coupled with social media use, learning is ubiquitous as
our students can interact with content and study without designated learning locations (Gikas &
Grant, 2013). Now with widespread adoption and frequent use, treating social media as an after-
thought at our institutions is doing a disservice to the community on campus. We now need to
understand social media policies and current practices to inform how we guide social media use
and behavior in higher education.
Social media use is increasingly becoming a mainstream practice among our higher edu-
cation stakeholders, including students, staff, and faculty (Rodriquez, 2011; Tess, 2013). This
lends to a growing need to study and understand how social media platforms are organized. Digi-
tal interactions and user-driven communities are thriving in higher education before, during, and
after our learners arrive on campus. Although the adoption of social media platforms and appli-
cations has increased (Duggan, Ellison, Lampe, Lenhart, & Madden, 2014), these tools are often
3
not an integral part of the official institutional technology landscape. Similar to other organiza-
tions and social settings, grassroots activities at our institutions that use social media result in an
organic development of social practices, local dynamic structure, and self-regulation.
A number of scholars and scholar-practitioners in higher education have explored how
social media practices impact teaching and learning, specifically to understand the legal consid-
erations; social media guidelines for privacy, intellectual property, and copyright (Rodriguez,
2011); and how to effectively utilize these platforms to impact student engagement (Mastrodi-
casa & Metellus, 2013). More than 90% of faculty members are using social media for profes-
sional careers outside the classroom (Moran, Seaman, & Tinti-Kane, 2011), and over one-third
of faculty members have utilized social media for teaching (Seaman & Tinti-Kane, 2013). The
scholarship of teaching and learning with social media is currently focused on collaboration and
engagement (Graham, 2014; Al-rahmi, Othman, & Mi Yusuf, 2015; Zhen, Niiya, & Warschauer,
2015); diversity and inclusion (Daugird, Everett, Jones, Lewis, & White, 2015); self-regulated
and self-determined learning (Dignath-van Ewijk & Fabriz, 2015; Blaschke, 2014); teacher-
learner roles in online communities (Barber, 2014); motivation and self-efficacy (Bumguardner,
Strong, Murphrey, & Dooley, 2014); and presence and community (Kear, Chetwynd & Jefferis,
2014; Kim, 2015). Higher education administration has researched social media with regards to
directing marketing and communications plans (Constantinides & Zinck Stagno, 2011), adoption
of platforms and use between campus stakeholders (Roblyer, McDaniel, Webb, Herman, &
Witty, 2010), improving adjustment to college (DeAndrea, Ellison, LaRose, Steinfield, & Fiore,
2012), effective recruitment and admissions strategy (Uversity, 2013), supporting learners’ aca-
demic transition (Ruud, 2013), and engagement of university alumni for crowdfunding cam-
paigns (Council for Advancement and Support of Education, 2014). Social media presents a new
4
challenge to the formal education system established in higher education (Selwyn, 2012). Social
media can be used beyond innovative pedagogies and student engagement, to impact how admin-
istrative personnel and academics function in higher learning. In understanding social media use
within our institutions, higher education can explore affordances to influence the processes and
shape communication strategies to encourage social interactions, share knowledge, and design
practices within an organization (Treem & Leonardi, 2012). There are a number of opportunities
where social media platforms can enhance work environments, offer professional development,
create collaborative networks, and support our job functions on campus. Higher education schol-
ars and administrators are repurposing social media platforms, like Twitter, to share information
and resources, request assistance, offer suggestions, expand learning opportunities beyond the
classroom, network with others, and develop a digital identity (Veletsianos, 2012). Currently we
see an increase of peer-reviewed publication sharing via social media outlets, such as Twitter,
(Darling, Shiffman, Côté, & Drew, 2013), specifically with regards to academic influence and
the potential impact scholars create through public engagement and meaningful contributions
within digital social networks (Stewart, 2015).
Social media has a number of positive attributes stemming from the ability to communi-
cate and engage institutional stakeholders; however there are also an increasing number of chal-
lenges and threats for our campus community. A number of colleges and universities are seeing
the need to establish guidelines around social technologies (Snyder, 2014) as institutions are
struggling with how to handle online behavior and how to manage abuse and cyberbullying on
social media (Luker, 2015). Based on the implications of social media functionality, including
content management, data privacy controls, conversation velocity, monitoring the sentiment and
reach, immediacy of the shared content, membership rules, and support for the network of rela-
5
tionships (Kietzmann et al., 2011), it is important that post-secondary education institutions de-
vise a set of standards to govern these functions.
In considering community standards and appropriate behavior, higher education organi-
zations have increasingly witnessed a number of challenging incidents on social media, including
racist and sexist Twitter attacks (Jaschik, 2014), termination of faculty due to online hate speech
(Mackey, 2014), cheating on exams (Fabris, 2015), student plagiarism (Glendinning, 2014), cy-
berstalking and sexual assault threats (Jouvenal & Shapiro, 2015), and reactions to campus inci-
dents that have gone viral on social media (Kingkade, 2015). Campus stakeholders expect the
institutions to regulate and intervene for these incidents, yet few college and university campuses
have protocols set out to do so. Specific scholarly standards need to be reviewed for ethical re-
search considerations and implications using social media platforms (Sandvig, 2015) as demon-
strated by the Facebook social network experiment (Kramer, Guillory, & Hancock, 2014). Le-
gal, ethical, and academic integrity issues continue to occur with social media use in higher edu-
cation. For example, in Tatro v. University of Minnesota (2011), a student in the mortuary sci-
ence program at the University of Minnesota created a number of Facebook postings on her ac-
count that included colloquial and lewd speech targeted toward cadavers and other unnamed in-
dividuals from her academic work. Also, a number of legal and ethical cases have arisen in re-
search and applied post-secondary educational programs (see, Giordano & Giordano, 2011; La-
sorsa, Lewis, & Holton, 2012) that require further considerations of social media use and regula-
tion. Other considerations for social media policy might include data breaches and cyber hacks
(Puri, 2014), and how existing laws, such as freedom of speech (Perrino, 2015; Grusin, 2015),
impact higher education organizations and their stakeholders who want to ensure safety for any
threats posted on social media related to exercising their first amendment rights (Logan, 2015;
6
Johnson & Woelfel, 2015). Finally, the issues of personal and professional boundaries in social
media platforms, with regards to the policies, are unclear. Academics find value in maintaining
appropriate and meaningful connections in these online, networked spaces; however the tension
of sharing personal and professional identities in openly on social media is constricted with the
boundaries of perception from the field and their own institutions (Kimmons & Veletsianos,
2013). For example, the professional organization NASPA, which supports student affairs edu-
cators in higher education, responded to an incident of anonymous abuses and attacks via confer-
ence participants shared on Yik Yak at their last annual meeting (Thomason, 2015). With arrests
being made for terrorist threats on such anonymous social media applications (Martellaro, 2015),
institutions of higher learning are more invested in holding members of their campus accountable
for online behavior and identifying appropriate online community standards.
In response to the aforementioned challenges and issues, higher education organizations
are establishing policies to guide the behavior and use of social media. Those institutions that do
not have a set policy are now in the process of creating protocols and guidelines for social media,
while other organizations are reviewing their protocol and standards. Even though a collective
knowledge seems to exist around social media policies, such knowledge is not well understood
by all higher education stakeholders and rarely studied by researchers. It is a critical time to
evaluate current social media policies and practices to scaffold administration and support at our
post-secondary education institutions.
Social Media Policy in Higher Education
As social media user engagement increases (Duggan et al., 2014), policy adoption is be-
coming a requirement for a number of colleges and universities. Often these social media proto-
cols and practices outline guiding principles, and provide safeguards against potential threats to
7
the institution or its community members. Social media policies, at the organizational level, are
a key piece of actualizing “the impact of organizational norms, policies, strategies and practices
that shape adoption strategies” (Mergel, Mugar, & Jarrahi, 2012, p. 152). Therefore we expect
social media policy documents to reflect institutional norms, policies, strategies and practices in
higher education. A number of corporate policies and practices have been adapted to meet the
needs of higher education with regards to social media. Following the implementation approach
for social media policy by the government, post-secondary education institutions should also of-
fer democratic participation, engagement, co-production, crowdsourcing solutions and innova-
tions on social media platforms (Bertot, Jaeger, Munson, & Glaisyer, 2010). These are critical
times to understand the existing regulatory frameworks for social media use, and to highlight the
opportunities and challenges they bring about (see, Bertot, Jaeger, & Hansen, 2011). To effec-
tively support student success and institutional goals, higher education administrators need to
create strategic plans, write official policies, and develop workshops to guide students, faculty,
and staff.
Prior studies have shown evidence of the need to review social media guidelines and poli-
cies within higher education, specifically with regards to privacy concerns and permissions
(Joosten, Pasquini, & Harness, 2013; Kind, Genrich, Sodhi, & Chretien, 2010). Kaplan and
Haenlein (2010) identify social media platforms that support certain types of online content, ac-
cessibility needs, and integrative communication plan. Other research studies in post-secondary
education assessed the presence of a public social media policy and how it addresses use for US
medical schools (Kind et al., 2010), review of the NCAA policies and legal implications for
monitoring student athletes’ social media activity (Epstein, 2012; Sanderson, 2011), evaluation
of social media training programs to guide at AACSB-International-accredited business schools
8
(Eaton, Luse, & Hodge, 2012), critical discourse analysis of social media text in higher education
policy documents from intuitions in the United Kingdom (McNeill, 2012), and evaluation of in-
stitutional efforts to guide social media use (Joosten et al., 2013). The findings from these re-
search studies make a number of valid points; however there is no common reference to capture
the shared understanding of social media policies in higher education. The purpose of this study
is to explore the existing body of social media policy and guideline documents, and identify key
components of meaning that contribute to the tacit structure of combined institutional knowledge
on the nature and use of social media in higher education. By reviewing social media protocols
as an instance of technological innovation within higher education institutions, this research will
help identify a roadmap towards sociotechnical stewardship framework to support long term
planning and strategy in organizations.
A Field Study of Social Media Policy Documents
The objective of this research is to examine the body of social media policy documents at
higher education institutions, determine the components of meaning that guide its underlying
structure, and present this structure in the form of a policy reference and an organizational frame-
work. While previous studies have reviewed social media policies for particular domains (see,
Eaton et al., 2012; Epstein, 2012; Sanderson, 2011), we intend to produce a generalized outcome
of broader organizational implications. Our method involves topic extraction using latent seman-
tic analysis (LSA) to determine the meaning in text (Landauer, 2014). This quantitative, text
mining method offers an effective approach for analyzing a document collection in unstructured
text format (corpus). For further details on the implementation of LSA see Kintsch and Man-
galath (2011) and Evangelopoulos, Zhang, and Prybutok (2012).
Data collection. A dataset of 250 publically accessible social media policy documents
9
from higher education institutions in 10 countries was compiled in early 2014. To gain a com-
prehensive perspective of the social media policy landscape, rather than selecting a sample of
specific documents, we made an effort to collect all documents offering policies, strategies,
guidelines, and regulations for social media use on campus. Through our search and outreach ef-
forts in the higher education sector, we found documents at three levels of policy development:
informational items, guidelines, and protocols. For this study we focused on English-language
documents. The corpus of 250 documents was first split into 24,243 individual passages to allow
the unstructured text to be organized appropriately for LSA. We manually pre-processed the
documents to ensure each single idea, such as a bullet point, paragraph, title, or statement, was
separated into self-contained passages, and all non-relevant data was removed, that includes pho-
tos, URLs, images, and embedded objects. Table 1 lists the number of policy documents and
passages represented by each country in this sample. For further information about this dataset
we refer the reader to (Psquini, 2016) to review the itemized list of specific higher education in-
stitutions, institutional type, student enrollment, and links to current social media policy and
guideline documents.
Table 1
Higher education social media policy corpus.
Geographic Region Documents Passages
United States of America 189 17,429
Canada 32 3771
United Kingdom 11 1121
Australia 8 1071
New Zealand 3 314
South Africa 1 189
Ireland 2 160
Netherlands 2 109
Norway 1 62
10
Austria 1 13
Total 250 24,243
Analysis and results. We started by completing the text preparation and term filtering
steps outlined in Coussement and Van Den Poel (2008). Since our goal was to understand the la-
tent semantic structure of our corpus, we implemented the factor analysis variant of LSA
(Sidorova, Evangelopoulos, Valacich, & Ramakrishnan, 2008). The overall outcome of our im-
plementation of LSA was to extract a rotated 36-factor solution of common topics shared among
the policy passages. Following the main LSA steps outlined in Kulkarni, Apte, and Evan-
gelopoulos (2014) and Evangelopoulos, Ashton, Winson-Geideman, and Roulac (2015), we list
the steps of our analysis below.
LSA step 1: Compilation of the term frequency matrix. The first step of the analysis is
to use software that parses each passage into individual words, and remove trivial English terms
such as and, at, the, as well as low frequency terms. Open-source R package tm and proprietary
commercial software package SAS® Text Miner, available free of charge to academics (SAS,
2016) are two choices that can accomplish these goals. It is also a standard practice to stem the
words and conflate terms such as educate, educated, educates, and education. This can be done
using R package SnowballC or SAS Text Miner. Following standard text mining practice, the
raw term frequencies were weighted using a transformation called inverse-document-frequency,
which boosts the frequency of rare terms and suppresses the frequency of common terms. We fi-
nally ranked all remaining terms by their ability to explain variance in the term frequency matrix
and retained the top terms that explained 95% of variance in a space of 100 principal components
(Evangelopoulos et al., 2012; Sidorova et al., 2008). At the end of this step we had a vocabulary
of 664 stemmed terms and a 664-by-24243, term-by-passage frequency matrix. The top six
11
terms (with their raw frequency and explained variance in parentheses) included: facebook (862,
2.71%), twitter (634, 2.30%), post- (1963, 2.13%), use- (1769, 2.02%), content (1105, 1.80%),
and account (1024, 1.70%).
LSA step 2: Decomposition. The term frequency matrix was subjected to singular value
decomposition (SVD), which is a generalization of principal component analysis appropriate for
two sets of variables (here, the set of 664 terms and the set of 24243 passages). SVD can be per-
formed using R package LSA or SAS Text Miner. See Evangelopoulos et al. (2015), appendix B
for related programming details in R and appendix C for related programming steps in SAS Text
Miner. The products of this step were a set of term loadings and a set of passage loadings on the
extracted latent semantic dimensions.
LSA step 3: Dimensionality selection and rotation of the dimensions. Following Kulka-
rni et al. (2014) and Evangelopoulos et al. (2015), we produced a scree plot of the eigenvalues.
An “elbow” point was identified at k = 36, therefore 36 factors were retained. The factor load-
ings were rotated using varimax rotations (Visinescu & Evangelopoulos, 2014).
LSA factor labeling. To understand the meaning of the extracted factors, we examined
the two sets of factor loadings, that is, the loadings for terms and the loadings for passages. Each
factor was then labeled based on the related high-loading terms and passages. Two researchers
labeled all 36 factors independently and discussed initial discrepancies until a consensus was
reached. Overall, the factors were easy to understand, as the high-loading passages for each fac-
tor were very similar, and the labeling process was completed without controversy. Table 2
identifies the universal 36-factor solution and the corresponding high loading passage count.
12
Table 2
The 36 extracted topics.
Topic Topic Label Count
F36.12 Institutional Users 740
F36.7 Information Management 735
F36.10 Page and Group Administration 707
F36.13 Account Management 684
F36.11 Support at Institution 664
F36.9 Comments 652
F36.5 Content 611
F36.1 Facebook 595
F36.2 Twitter 592
F36.19 Social Networking 578
F36.20 Video, Audio and Photo Sharing 546
F36.8 Posting 539
F36.14 Use of Platforms 518
F36.3 Engagement 517
F36.23 Institutional Identity 510
F36.22 Site Maintenance 486
F36.4 Best Practices 474
F36.24 Followers 464
F36.21 Audience 451
F36.27 Link 442
F36.16 Blogs 439
F36.25 Time and Resource Management 431
F36.29 Naming Conventions 427
F36.17 Copyright and Fair Use 422
F36.32 Strategy 414
F36.26 Official Institutional Presence 405
F36.18 Personal Use 398
F36.30 Digital Identity Management 380
F36.31 Terms of Service 378
F36.6 YouTube 374
F36.15 Respect 367
F36.28 Privacy 349
F36.35 Responsibility 345
F36.36 Advice, Resources and Questions 308
F36.33 Flickr 286
F36.34 LinkedIn 244
To share a common understanding of the social media policy document semantic struc-
13
ture and develop operational knowledge of these domains in practice, we utilized Noy and
McGuinness’ (2001) ontology-development method to label these topics, and then further exam-
ined the relationships and variability among the topics within this corpus. To understand the rela-
tionships among the social media policy corpus, specifically among the 36 extracted topics, we
conducted further investigations to examine the differences between topics and institutions and
variability of topics themselves within these documents.
A correspondence analysis was akin to a weighted principal components analysis, where
a contingency table was developed to partition the total variance similar to the chi-square test for
association and analyzed. In looking at all 36 factors in relation to the policy’s country of origin,
that is, documents from higher education institutions located in Australia (AUS), Austria (AUT),
Canada (CAN), Great Britain (GBR), Ireland (IRE), the Netherlands (NLD), Norway (NOR),
New Zealand (NZL), the United States (USA), and South Africa (ZAF), this analysis identified
the topics that are closer in relation to one another and the specific country. In further analysis of
the topic dimensions, we examined the expected and the actual existence of a particular topic in a
policy document within the country via these geographic regions. The ten countries identify 14
social media policy topics on which topic distributions across countries have maximum differ-
ences. We name these divergent topics (see Tables 3 and 4).
14
Table 3
Divergent Topics: Observed Passage Frequencies
Topic T# AUS AUT CAN GBR IRE NLD NOR NZL USA ZAF
Content T05 52 0 91 20 5 9 0 19 598 51
Official Institutional Presence T26 50 0 65 19 0 0 6 2 458 40
Institutional Users T12 102 0 165 93 17 0 2 9 629 10
Account Management T13 68 0 103 9 5 4 0 31 686 2
Link T27 10 0 97 25 5 1 1 9 413 18
Responsibility T35 18 0 42 37 5 5 2 17 327 6
Privacy T28 20 0 122 10 4 1 0 4 281 0
Social Networking T19 38 0 118 49 19 10 1 4 512 0
Information Management T07 60 0 229 46 6 6 1 11 736 6
Terms of Service T31 42 0 52 27 5 0 3 7 353 4
Page & Group Administration T10 8 2 105 16 1 3 2 4 798 0
Copyright and Fair Use T17 37 0 49 23 3 1 0 11 355 1
Site Maintenance T22 37 0 138 20 3 1 5 0 521 9
Use of Platforms T14 43 0 114 55 4 2 1 15 564 1
Totals 585 2 1490 449 82 43 24 143 7231 148
Table 4
Divergent Topics: Expected Passage Frequencies Under the Hypothesis of No Association
Topic T# AUS AUT CAN GBR IRE NLD NOR NZL USA ZAF
Content T05 48.5 0.2 123.
537.2 6.8 3.6 2.0 11.9 599.
212.3
Official Institutional Presence T26 36.7 0.1 93.5 28.2 5.1 2.7 1.5 9.0 453.
89.3
Institutional Users T12 58.9 0.2 150.
145.2 8.3 4.3 2.4 14.4 728.
314.9
Account Management T13 52.1 0.2 132.
740.0 7.3 3.8 2.1 12.7 643.
913.2
Link T27 33.2 0.1 84.6 25.5 4.7 2.4 1.4 8.1 410.
68.4
Responsibility T35 26.3 0.1 67.1 20.2 3.7 1.9 1.1 6.4 325.
56.7
Privacy T28 25.4 0.1 64.6 19.5 3.6 1.9 1.0 6.2 313.
46.4
Social Networking T19 43.1 0.1 109.
733.1 6.0 3.2 1.8 10.5 532.
610.9
Information Management T07 63.2 0.2 160.
948.5 8.9 4.6 2.6 15.4 780.
816.0
Terms of Service T31 28.3 0.1 72.0 21.7 4.0 2.1 1.2 6.9 349.
67.2
Page & Group Administration T10 53.9 0.2 137.
241.3 7.6 4.0 2.2 13.2 665.
913.6
Copyright and Fair Use T17 27.5 0.1 70.1 21.1 3.9 2.0 1.1 6.7 340.
47.0
15
Site Maintenance T22 42.1 0.1 107.
332.3 5.9 3.1 1.7 10.3 520.
510.7
Use of Platforms T14 45.8 0.2 116.
835.2 6.4 3.4 1.9 11.2 566.
611.6
Totals 585 2 1490 449 82 43 24 143 7231 148
In looking at the actual frequencies (Table 3) versus the expected frequencies (Table 4) of
these 14 topics, there are a few countries where a particular topic is mentioned more frequently
than what would be expected based on the sample sizes alone. For example, Institutional Users
(T12) is emphasized in Australian institutional policy. Also, Canadian higher education institu-
tions emphasize Privacy (T28) and Information Management (T07) more often then their peers
in this study. One rationale for the emphasis on privacy in Canadian university and colleges,
could be the Privacy Act, as well as increased support for Anti-Spam legislation across the coun-
try. In contrast, Great Britain and Canada do not include Official Institutional Presence (T26) in
their policy documents as frequently as their American peer institutions. One possible reason for
this might be the fact that colleges and universities in the United States tend to manage brand and
digital identity on campus based on their athletic programs, which involve heavy use of social
media.
In looking at a histogram comparison of topics covered by institutional type, a large por-
tion of policies includes fewer than 50% of the topics covered by all institutions. Specifically,
when comparing the social media policy topics by country, there are notable differences as
shown in Figure 1.
----------------------------------
Insert Figure 1 here
----------------------------------
Figure 1. Comparison of number of topics addressed in social media policy documents by coun-
16
try.
Referring to the box plots in Figure 1, the line inside each box is the median number of
topics mentioned in the policy documents. The two ends of each box are the 25th and 75th per-
centiles, respectively. The whiskers show the range for the number of topics addressed in each
country’s policy documents. For example, higher education institutions in Canada have policy
documents that cover anywhere from 6 to 36 of the extracted topics listed in Table 2. The median
topic coverage in Canada is about 28, the 25th percentile is about 18 and the 75th percentile is
about 32. Topic coverage in the United States is very similar to that in Canada. In contrast, topic
coverage in New Zealand is much smaller than topic coverage in either Canada or the United
States with the median number of topics covered being equal to 16.
Finally, to investigate the topic relationships in the corpus, we reviewed a 36-by-36-topic
correlation matrix (Masked Reference, 2016) to look for patterns and connections among the so-
cial media policy topics. Among various pairs of topics, we see high correlations between social
media policy topics, such as Audience (T21) and Engagement (T03), where the Pearson’s corre-
lation coefficient is r = 0.588, and Best Practices (T04) and Strategy (T32), where r = 0.587. This
is not surprising, as a number of policies crafted by corresponding campus divisions offer direc-
tives for communication, marketing, and public relations use of social media channels.
Interestingly, topics for encouraging campus community development and planning at the
institution were highly correlated with one another. For example, Strategy (T32) and Engage-
ment (T03), had r = 0.753. This is a testimony to the strategic importance of user engagement.
Another interesting highly correlated pair is Information Management (T07) and Digital Identity
Management (T30), with r = 0.553, which links operational and branding aspects of information.
Finally, considering how highly correlated Privacy (T28) and Information Management (T07)
17
were (r = 0.891), it is a critical time for higher education institutions to organize governance and
legal directions for an environment that manages information with a strong consideration of pri-
vacy.
Overall, this LSA method allowed for a large number of social media policy document
passages to be synthesized to reveal 36 universal topics. This analytical approach allowed us to
review documents from 250 higher education institutions and determine common practices and
applications of social media protocols among the ten countries included in the study. Referring
back to the 36 universal topics presented in Table 2 and in looking at the analysis of association
(Tables 3 and 4), box plots (Figure 1), and correlation analysis of policy topics, we noticed cer-
tain high-level themes emerging from the extracted topics. These helped us synthesize a frame-
work, built around six central themes outlined in Figure 2: governance, standards, guidance, le-
gal consideration, community development, and research and reporting.
----------------------------------
Insert Figure 2 here
----------------------------------
Figure 2. Sociotechnical stewardship framework for higher education.
Discussion: The Roadmap to Sociotechnical Stewardship
The results of the social media policy document study identify how organizations regu-
late behaviors and use related to social technologies within the higher education sector. This re-
search provides a central point for evaluation and development of protocols for post-secondary
education institutions that want to learn about best ways to support and manage social media ex-
changes. This study developed a comprehensive database (Masked Reference, 2016), curated
18
with guidelines, strategies, and ideas for social media regulation directed towards students, staff,
and faculty. In addition, it identified 36 topics (see Table 2) universally addressed among the 250
higher education institutions. This high-level view of the social media policy documents, not
only draws out the critical components found within the individual policy passages, it also sets a
path to develop a broader framework to support social technologies within higher education or-
ganizations and their stakeholders.
For both interpretation and support of technical policies, it is up to the administration in
higher education to become sociotechnical stewards. In communities of practice (Wenger, 1999),
stewarding is the developmental process that supports technological environments that the com-
munity has constructed, to scaffold work and learning (Wenger, White, & Smith, 2009). This
creative role essentially negotiates and sustains community-wide digital practices while consider-
ing the capacity for both its members and their projects. Stewards become involved in supporting
community members’ use of technology, especially with regards to technology acquisition, shar-
ing effective practices, and ensuring continuity with minimal disruptions. Stewards are partially
responsible for maintaining the responsiveness of a technology, and they should also “attend . . .
to community boundaries created by technology” (Wenger et al., 2009, p. 243). The capacity to
steward may be distributed widely throughout a higher learning organization, specifically tar-
geted at one or two people or within a team. The concept of stewarding may become institution-
alized or adopted formally; however organizations may choose to keep this role participatory or
emergent, depending on the context and need for sociotechnical support.
Although this research attempts to bring clarity to social media guidance, the synthesis of
these policy documents offers further insights and considerations for organizations interested in
supporting sociotechnical systems. It is the stewarding campus stakeholders, that is, the commu-
19
nities of practice in higher education intuitions, where these policies are framed to provide so-
ciotechnical support. The sociotechnical stewardship framework presented in Figure 2 is de-
signed to scaffold digital exchanges between the organization, its members, and the emerging
technologies mediating their interactions. Such interactions should be managed according to the
suggested ontology for sociotechnical stewardship with the following categories in the ontologi-
cal class hierarchy: governance, standards, guidance, legal consideration, community develop-
ment, and research and reporting.
Sociotechnical systems impact more than one single unit or department within a higher
education institution. Stewardship of sociotechnical matters is critical more than ever in post-
secondary education. This central model focuses on the need to identify and connect these
pieces within an organization for effective collaboration across units, to promote clear communi-
cation and standard business workflow practices, to advance development at the institution, and
to effectively meet the needs of higher education stakeholders. Social media policy documents
reflect institutional norms, policies, strategies, and practices, as mentioned earlier in the Social
Media Policy in Higher Education section of this paper. The next section will discuss the so-
ciotechnical framework components and their specific content. The framework encourages orga-
nizations to align their institutional planning objectives strategically, gain administrative support,
establish resources, implement governance, and sustain technical systems/platforms, while pre-
serving networks and alliances.
Governance. Higher education administration will want to form an advisory group to es-
tablish and/or revise policy documents. In connecting to central ideas around stewardship
(Wenger et al., 2009), this is often a few key individuals or a division to represent this process.
This might be a central council or standing-committee appointed by central administration; how-
20
ever being inclusive of represented stakeholders from the community. With regards to gover-
nance, organizations should discuss the policy topics information management (F36.7) require-
ments, the naming conventions (F36.29) of the organization, and the official institutional pres-
ence (F36.26) or brand as outlined by organizational mandates and identity management require-
ments.
Standards. This area establishes the provision of policies and protocols, which includes
the implications to any infractions of these regulations. It is critical to identify current policy
documents and regulations that already apply, and those that might require revisions for so-
ciotechnical considerations. Policy topics extracted related to this area might include use of plat-
forms (F36.14) or even directed at specific institutional users (F36.12), specifically targeted at
implications for particular behavior and/or use. Many organizations typically have applicable
protocols; however they might need to expand the scope or language of these established docu-
ments to allow for a broader interpretation of the policy.
Legal considerations. In relation to standards, sociotechnical stewardship should include
legal considerations related to human resource requirements, security compliance, and agree-
ments, and local/federal statues that might impact the organization. Institutions need to consider
how existing laws (see, Grusin, 2015; Perrino, 2015) also impact sociotechnical needs for the
campus stakeholders. It will also be important to adhere to risk management benchmarks, copy-
right agreements, and fair use standards. Higher education does little to guide the legal issues of
social media use, with regards to privacy, intellectual property, and copyright (Rodriquez, 2011);
so it is not surprising that information management, privacy, and support at the institution were
three of the fourteen divergent topics listed in policy documents (Pasquini & Evangelopoulos,
2015). Often these topics can be found in local legislation and compliance protocols at institu-
21
tions. Related policy topics found under legal considerations include terms of service (F36.31)
agreements from technology companies, and privacy (F36.28) considerations for institutional
stakeholders and/or the geographic location of the organization.
Guidance. As the organization sets both standards and legal considerations, it will be im-
portant to support the implementation of these items. Joosten et al. (2013) discovered that cam-
pus stakeholders felt a lack of support by and from the institution, with regards to social media.
On-going learning, training, and development would help establish guidelines and organizational
help, which was addressed in the following policy topics: best practices (F36.4), digital identity
management (F36.30), account management (F36.13), advice, resources, and questions (F36.36),
and to identify the contact or specific support at institution (F36.11) or within the organization.
A glossary of terms might include definitions, ideas about accessibility, other examples, and us-
ability strategies for sociotechnical systems. Institutions need to broaden technological and peda-
gogical practices to consider how these tools and systems impact ideas, practices, and training
plans (Georgina & Hosford, 2009). It will be critical for higher learning organizations to consider
the implications social technologies will impose upon curriculum development, personnel train-
ing, and enhancing learning environments.
Community development. As technology and individuals interact, it will be critical to
consider how to engage and involve the higher education stakeholders. It will be desirable to es-
tablish a level of respect and responsibility, to encourage accountability for community mem-
bers. Community development moves beyond the training and learning aspects of the technolo-
gies, to involve topics such as acceptable personal use (F36.18), targeting communication for rel-
ative audiences (F36.21), and encouraging social networking (F36.19) and a certain level of en-
gagement (F36.6) with technology among members of the organization. For sociotechnical
22
stewardship to be effective in this area, both strategy (F36.32) and respect (F36.15) must be
taken into consideration when planning desired interactions.
Research and reporting. To monitor and review progress, it will be important to re-
search and report sociotechnical progress within the organization. To sustain and administer the
use of technologies, institutions should be encouraged to develop a directory or repository of all
technical tools and systems. This allows others to connect and share information in a uniform
manner, and encourages networks and alliances within the organization. Data analytics and data
share captures sociotechnical performance metrics, and it also allows others to learn from others
and build upon experiences across the organization. By establishing a central reporting and re-
search area, this streamlines knowledge for use of platforms (F36.14), site maintenance (F36.22),
and time and resource management (F36.25) awareness to sustain particular organizational re-
sources that align with the strategic plan.
The impact and influence of sociotechnical systems continue to thrive in our colleges and
universities. As post-secondary education includes social media for learning and teaching re-
sources to increase engagement and motivation (Cooke, 2015), institutions are increasingly
adopting open educational resources such as open textbooks (Fisher, Hilton, Robinson, &Wiley,
2015) and new models for online learning, such as massive open online courses (Yuan & Powell,
2013). Beyond instructional design considerations, higher education administrators and policy
makers should utilize this sociotechnical stewardship model for long-term planning and strategic
visioning. This framework helps higher learning institutions to examine the technological infra-
structures that weave social dynamics into campus culture. Future studies in higher education,
examining technology and social media, may also decide to utilize the sociotechnical steward-
ship framework to guide inquiry and support research design. Suggestions for further investiga-
23
tion might include utilizing the six areas of the framework to guide evaluation strategies for de-
partments or divisions, interview questions for senior administration, campus-wide assessments
to determine infrastructure gaps, and comparative case studies to review policy and practice
among higher learning institutions.
Conclusion
The resulting sociotechnical framework highlights the interaction of technology and hu-
mans, within an organizational environment. Social technologies and the use of social media al-
low college and university stakeholders to communicate, share knowledge, learn, and interact
with one another. Furthermore, potential engagement and community development occurs that is
woven into our campus environments regardless of location and should be guided by a sociotech-
nical steward.
In analyzing 250 higher education social media policy documents, we were able to deter-
mine shared components of meaning by extracting 36 factors that create the semantic structure of
this corpus. By making the corpus publically accessible (Pasquini, 2016), we believe this open
access resource offers practitioners and organizations, from higher education and other indus-
tries, a common reference point for developing social media policies and practices appropriate
for their organizational stakeholders. We share this open dataset to encourage other scholars to
expand upon this research to understand the effect of policy into practice and to evaluate how so-
cial media policies influence individuals and impact community culture within the higher educa-
tion. Research findings from this study identify:
Social media adoption and use is widespread in the post-secondary education sector;
Frequent behavior and misuse incidents on social, open technologies raise the need for in-
stitutional standards and protocols in higher education;
24
A dataset of 250 higher education institutional social media policy documents; represent-
ing 10 countries with universal governance suggestions are available for reference and re-
view;
A text analytic method of extraction helps to determine policy topics to inform social me-
dia governance and practice; and
The sociotechnical stewardship framework for strategic technology planning with empha-
sis on: governance, standards, guidance, legal consideration, community development,
and research and reporting.
The methodological approach presented in this paper can be applied on other policy do-
mains well beyond social media policy. In higher education alone, it is possible to review text
within a student code of conduct or even an employee handbook to extract topics.
Subsequent to understanding the semantic structure of social media policies, we estab-
lished a framework for sociotechnical stewardship in our higher education organizations. This
high-level framework can guide the sociotechnical interactions between organizations and their
internal and external stakeholders, far beyond the scope of higher education institutions and the
use of social media applications. Continuous research on sociotechnical systems and steward-
ship, with regards to emerging technologies in general, can determine how these technologies are
impacting organizational environments, infrastructures, and stakeholders.
One limitation of this study is that we only conducted document analysis and did not ex-
amine how documents are brought into practice in higher education. It would be helpful to ex-
amine the practices and implications of these regulations.
Future research in this area of study might include the consultation of higher education
administrators and managers who support social media policy documents to further understand
25
the business processes and procedures for implementation of the policy within the organization.
Future studies in higher education, examining technology and social media, may also decide to
utilize the sociotechnical stewardship framework to guide inquiry and support research design.
Suggestions for continued research investigation might include utilizing the six areas of the
framework to guide evaluation strategies for departments or divisions, interview questions for se-
nior administration, conduct campus-wide assessments to determine infrastructure gaps, compare
these policy documents with other higher education policy, and complete comparative case stud-
ies to review policy and practice among higher learning institutions.
26
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... This tension appears to play out in the SM policies of HE institutions. Pasquini and Evangelopoulos (2017) examined 250 SM policies from HE institutions around the world. They teased out 26 "universal topics" that describe the kinds of topics that SM policies tended to contain in HE. ...
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