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A Social Networks Approach to PublicRelations on Twitter: Social Mediatorsand Mediated Public RelationsDr. Itai Himelboim a , Guy J. Golan b , Bitt Beach Moon c & Ryan J.Suto ba Department of Telecommunications , University of Georgiab Newhouse School of Public Communications , Syracuse Universityc Hankuk University of Foreign Studies , Republic of KoreaPublished online: 19 Aug 2014.

To cite this article: Dr. Itai Himelboim , Guy J. Golan , Bitt Beach Moon & Ryan J. Suto (2014) A SocialNetworks Approach to Public Relations on Twitter: Social Mediators and Mediated Public Relations,Journal of Public Relations Research, 26:4, 359-379, DOI: 10.1080/1062726X.2014.908724

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A Social Networks Approach to Public Relations onTwitter: Social Mediators and Mediated Public Relations

Dr. Itai Himelboim

Department of Telecommunications, University of Georgia

Guy J. Golan

Newhouse School of Public Communications, Syracuse University

Bitt Beach Moon

Hankuk University of Foreign Studies, Republic of Korea

Ryan J. Suto

Newhouse School of Public Communications, Syracuse University

This study proposes theoretical and practical frameworks to systematically examine mediated public

relations in social media spaces. We applied a social network conceptual framework to identify and

characterize social mediators that connect the US State Department with its international public. The

results showed that social mediators vary in terms of their formality and interdependence. Formal

social mediators were primarily US government agencies while informal social mediators were non-

governmental organizations (NGOs) and individuals. Notably, relationships with populations in the

Middle East and North Africa were mediated primarily by informal actors, and formal mediators

played a key role in connecting the public with everywhere else in the world. Government-related

formal mediators and informal social mediators showed similar levels of bilateral relationships. In

contrast, news media, the most traditional public relations mediators, were rarely found as social

mediators and demonstrated the most unilateral relationships.

Social media are platforms for interaction and information exchange, where issues are debated

and defined (Park & Reber, 2008). This enables public relations researchers to scan the various

forms of interaction (Kelleher & Miller, 2006), as well as to evaluate tangible relationship out-

comes (Porter, Sweetser Trammell, Chung, & Kim, 2007). There is a general consensus among

public relations scholars that new interactive media have great potential to make communication

more strategic, two-way, interactive, symmetrical, or dialogical (J. E. Grunig, 2009; Kelleher,

2006, 2009; Kent, Taylor, & White, 2003). In addition, cultivating relationships through social

Correspondence should be sent to Dr. Itai Himelboim, University of Georgia, Department of Telecommunications,

101L Journalism Building, 120 Hooper St., Athens, GA 30602. E-mail: itai@uga.edu

Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/hprr.

Journal of Public Relations Research, 26: 359–379, 2014

Copyright # Taylor & Francis Group, LLC

ISSN: 1062-726X print/1532-754X online

DOI: 10.1080/1062726X.2014.908724

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media has also been explored in public relations research (Eyrich, Padman, & Sweetser, 2008;

Levenshus, 2010; Sweetser, 2010).

However, there is still a need to further capture a whole social network structure in which an

organization and its various stakeholders consist of different relations. In public relations

research, little attention has been paid to illustrating a holistic relational structure from a

macro-perspective (Sedereviciute & Valentini, 2011). As argued by Sommerfeldt and Kent

(2012), examinations of organization relationships from a micro-organization to a single stake-

holder could fail to provide the full detail of the overall organizational social structure that a

macro-perspective may offer. As argued by Rowley (1997), organizational–stakeholder relations

cannot be fully understood via a didactic perspective. Rather, those relationships can be better

understood when considering the interconnectedness of relationships along with the location

of the organization within the larger relationship network. This argument is further reinforced

by Edwards (2012), who argued that public relations scholars have overemphasized the organi-

zation as the key object of research through the prevalent organization–public relationship

(OPR) paradigm. Our study aims to expand beyond this narrow perspective by identifying the

key role that third-party mediators play in a highly complex two-way communication social

media ecology where OPRs are understood through a multiobject holistic approach. In this

study, we aim to expand public relations scholarship by providing a more enhanced examination

of organizational–stakeholder relationship, which will expand our analysis beyond the OPR per-

spective to also examine the potential impact of third-party actors. More specifically, we aim to

evaluate the influence of social media mediators through a network analysis perspective.

Given that any entity can act as a social mediator with its power of distributing information, it

is imperative to illustrate how the interactive paths between an organization and its publics are

connected by influential mediators within a virtual space. Social networking sites such as Twitter

can be properly used to depict such structure and to identify social mediators because they form

different kinds of network structures, compared to traditional media or other kinds of Web pages

(Gilpin, 2010).

Our study proposes a conceptual framework that bridges core public relations concepts and

social networks literature. In particular, we apply a network approach to identify and classify the

types of mediators who connect organizations with their publics and the direction of communi-

cation between them. This study takes the US State Department as a case study to examine pub-

lic relations on Twitter. Ten data points were collected, consisting of users who posted messages

using the hashtag #SecClinton, the content of the messages, and the network of relationships

among these users. We apply network cluster analysis to identify subsets of users who interact

and communicate about the topic (i.e., clusters), the most connected users (i.e., hubs) in each

cluster, and the level of mutuality each hub has in terms of its relationship with its publics. This

study, then, aims to provide practical guidelines about how to evaluate Twitter activity with

respect to an effective mediated relationship.

LITERATURE REVIEW

Relationship building between organizations and key stakeholders via new interactive media,

including social media, has been a key area of interest for public relations scholars (Bortree

& Seltzer, 2009; Jo & Kim, 2003; Kent & Taylor, 1998, 2002; Kelleher & Miller, 2006; Searls

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& Weinberger, 2000; Seltzer & Mitrook, 2007). Particularly, Kent and Taylor (1998) defined

dialogue as ‘‘any negotiated exchange of ideas and opinions’’ (p. 325). They suggested that a

web-based relationship between an organization and its publics should encourage both conver-

sation between visitors and a dialogic loop between an organization and its publics. Such prin-

ciples have been widely applied to social media such as blogs (Seltzer & Mitrook, 2007) and

social networking sites (Bortree & Seltzer, 2009; Rybalko & Seltzer, 2010; Waters, Burnett,

Lamm, & Lucas, 2009).

However, some scholars found that many organizations still failed to effectively utilize the

dialogic strategies offered by social networking sites (Botree & Seltzer, 2009). Scholars suggest

that current dialogic principles may not be adequate for evaluating the features of social net-

working sites that characterize dialogic orientation (Rybalko & Seltzer, 2010). This might be

because there is little understanding of unique dialogic approaches tailored to social media sites,

considering their unique form of user (Finin et al., 2008; Gilpin, 2010).

Relationship and relationship-building are the cornerstones of public relationships (Botan,

1992; Broom, Casey, & Ritchey, 1997). The social networks theoretical approach focuses on

patterns of relationships among social entities. Therefore, exploring a network structure, which

consists of an organization and its publics interacting on social media sites, is essential for exam-

ining dialogic principles or relational strategies specifically tailored to social networking sites. In

the literature review next, we first discuss the importance of mediated public relations and social

mediators in public relations. Next, we discuss social networks and social media and conceptua-

lize the two public relations concepts in terms of patterns of social relationships in networks. We

conclude by introducing a case study and related research questions.

MEDIATED PUBLIC RELATIONS: SOCIAL MEDIATORS ANDBILATERAL RELATIONSHIPS

Traditionally, researchers used the notion of mediators in the field of public relations to describe

main entities (e.g., mass media), upon which public relations experts should focus for relation-

ship management (Kent & Taylor, 2002; Yang & Lim, 2009). Social media platforms have

transformed the very nature of relationship management as key mediators interrelate=interactbetween organizations and various stakeholders (Long et al., 2007; Hazleton et al., 2007;

Worley, 2007). B. G. Smith (2010) showed that social mediators may participate in public

relations through social networking sites even if they are nonpublic-relations practitioners.

Taken together, social mediators could be seen not only as key stakeholders or publics to be

targeted, but also as collaborators for dialogic relationships with other publics.

We define social mediators as the entities that mediate the relations between an organizationand its publics through social media and regard mediated public relations as communicativerelationships and interactions with key social mediators that influence the relationship betweenan organization and its publics. As argued by Edwards (2012), the traditional view of public

relations as an organizational management function is unlikely to provide scholars with a com-

prehensive perspective. The key reason for this limitation is the fact that public relations often

involve entwined relationships between multiple stakeholders (Coombs & Holladay, 2007). The

prevalence of social media as a relational sphere of interaction between not only organizations

and stakeholders, but also activists, organizational rivals, citizen bloggers, and journalists

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highlights the need for a more comprehensive perspective of public relations scholarship

(Coombs & Holladay, 2012; Sedereviciute & Valentini, 2011; Waters, Tindall, & Morton,

2012). We believe that our definition of social mediators, as identified by the network analysis

approach, can help advance this broader perspective.

TYPES OF SOCIAL MEDIATORS IN MEDIATED PUBLIC RELATIONS

Without social mediators, organizations are bound to communicate only with audiences that they

can reach directly (e.g., users who follow an organization on Twitter or users that are fans of thatorganization on Facebook). Because interaction among users in social media is based on social

interactions, social mediators can be categorized based on the way they interact with each other.

We focus on formality, as well as on interdependence in terms of social mediators’ interactive

style with an organization’s publics.

Formality: Formal and Informal Public Relations Mediators

Social mediators can be categorized based on their formality. These two types of mediators both

play an essential role in the interaction between organizations and with their various stake-

holders. Formal mediators are formal in the sense that they are either associated with an organi-

zation (e.g., an embassy that communicates its government’s agenda abroad) or hold a societal

role as information providers (e.g., news media). Informal social mediators are social actors who

are grassroots and are not associated with the organization or with other social institutions, such

as news media. By identifying social mediators and mapping out their interaction with organiza-

tions and stakeholders, public relations scholars can better grasp overall multidimensional rela-

tional dynamics.

Interdependence: Unilateral and Bilateral Mediated Public Relations

Contingency interactivity is regarded as ‘‘a process involving users, media, and messages,’’ in

which ‘‘communication roles need to be interchangeable for full interactivity to occur’’ (Sundar

et al., 2003, pp. 34–35). Kelleher (2009) suggested that facilitating contingency interactivity may

be a key strategy that affects relational outcomes. Therefore, social mediators may differ depend-

ing on the degree of involvement with their informative interaction. In other words, the ability to

form unilateral or bilateral ties can determine mediated public relations. Mediated public rela-

tions would be considered unilateral when social mediators allow other users to retrieve their

information but they do not initiate the connection to exchange information. Bilateral relations,

on the other hand, form when social mediators make connections interdependently by giving and

taking their information and creating interactive ties. Therefore, bilateral mediated public rela-

tions make dialogic communication more effective than unilateral mediated public relations.

Specifically, bilateral mediated public relations can enhance online relationship strategies

including communicated commitment and conversational voice. Communicated relational com-

mitment indicates ‘‘a type of content of communication in which members of an organization

work to express their commitment to building and maintaining a relationship’’ (Kelleher,

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2009, p. 176) and accounts for assurance and openness (Kelleher & Miller, 2006). When

bilateral ties are formed, social mediators can give organizations more paths to express their

legitimacy and offer publics more opportunities to discuss their opinions about organizations.

Additionally, communicated commitment can be a key factor that affects relational outcome,

as it accounts for assurances and openness (Kelleher & Miller, 2006). Therefore, it is important

to identify bilateral social mediators and to establish bilateral mediated public relations, rather

than only unilateral mediated public relations.

TWITTER AND PUBLIC RELATIONSHIPS

As the leading micro-blogging platform, Twitter has been recognized by public relations

professionals and scholars as an effective relationship-building tool (Evans, Twomey, & Talan,

2011). Indeed, Twitter’s relationship-building potential is enhanced by its ability to develop an

organization’s social media presence by linking to its profiles on other social networks, such as

Facebook and LinkedIn (Fischer & Reuber, 2011). Furthermore, media scholars have argued that

social media relationship-building can augment an organization’s overall social capital, which,

in turn, may provide organizations with positive tangible outcomes (Diga & Kelleher, 2009;

Taylor & Doerfel, 2003).

Recognizing Twitter’s potential for fostering bilateral relationships between organizations

and various publics, Rybalko and Selzter (2010) analyzed its use by Fortune 500 companies.

The results of their analysis indicate that most organizations underutilize the platform and its

capability to develop symmetrical two-way communication. Similarly, Waters and Jamal

(2011) found that, despite its capacity for two-way communication, many organizations are

using Twitter in a unilateral manner as an information-sharing platform, rather than one for

relationship-building.

The two core aspects within mediated public relations discussed so far are social mediators

and bilateral=unilateral relationships. At the core of these concepts is the idea that patterns of

relationships and social ties matter for public relations. Examining patterns of social relations

lie at the heart of the social networks theoretical approach. Thus, in the next section, these

two core concepts are conceptualized in terms of social networks.

SOCIAL NETWORKS AND PUBLIC RELATIONS

Broadly speaking, a social network is a structure created by social actors (i.e., nodes), such as

individuals and organizations, when social ties (i.e., links) are created between them. Social

media allow users to form symbolic relations with one another. Social network theories focus

on relational ties among social entities and on the patterns and implications of these relationships

(Wasserman & Faust, 1994). On social networking sites, users form networks by articulating a

list of other users with whom they share a connection. On Facebook, the most visible links are

formed by friendships. On Twitter, social networks are created by relationships of following, aform of subscription to others’ Twitter messages (Hogan, 2010).

Relationship and relationship-building, as previously indicated, are the cornerstones of public

relationships (Botan, 1992; Broom et al., 1997). The social networks theoretical approach, then,

is a natural form of understanding and evaluating public relations as it focuses on patterns of

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relationships among social entities. For public relations, one can examine the network of an

organization and the individuals who are included in its publics. When examining the use of

Twitter by organizations for establishing relationships with publics, two public relations con-

cepts can shed light on emerging network patterns: social mediators and bilateral relationships.

However, before the two are examined from a social networks perspective, we discuss the social

boundaries of Twitter relationships.

Clusters and the Social Boundaries of User-Interaction

Given the opportunity to interact freely, social actors create subgroups in which interconnections

are more prevalent than connections with others outside that subgroup (Granovetter, 1973; Watts

& Strogatz, 1998). Theoretical work in social and other networks has involved considerable

effort to uncover ways of dividing networks into their constituent subgroups (Wasserman &

Faust, 1999). Cliques and clusters refer to subgroups in a network in which nodes are substan-

tially more connected to one another than to nodes outside that subgroup (for more discussion on

clusters and cliques, see Carrington, Scott, & Wasserman, 2005). Clusters can also be seen as

community structures in networks (Newman, 2004). In the context of public relations on Twitter,

a user’s social network decides the tweets to which that user is exposed. Clusters on Twitter are

composed of dense subgroups of interconnected Twitter users that provide the channels through

which users are exposed to tweets. For example, users may talk about an organization, topic, or a

product. The sources of information may be within their cluster. Users are likely to either be

exposed directly (by following them) or indirectly, via their cluster-mates who may retweet

posted messages. A cluster on Twitter, then, determines users’ and organizations’ immediate

networks.

Social Mediators and Network Centrality

From a public relations standpoint, an organization that can reach its public either directly or via

mediators is traditionally considered to be a media organization. In a social network, an organi-

zation connects with the audiences closest to them—generally, those that are in their clusters.

However, to reach audiences in other clusters, organizations often need a mediator. Users that

play the role of a mediator take a unique position in the network, as they can link users across

clusters (Wasserman & Faust, 1999).

Mediated Public Relations and Bridging Hubs

Users can take unique structural positions in a network. These structural positions define the

roles that such users play in the network. Users in these positions are identified by measurements

of connectivity. One of the most common set of measurement used to identify users in unique

positions is centrality measurements. Centrality refers to how prominently connected an actor is

in a network. Centrality helps to explain the extent to which an individual or organization is con-

nected to others in their environment (Freeman, 1979; Wasserman & Faust, 1999). There are

several types of key structural roles that users can play in a network, but only two are relevant

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to this article: a bridge or a brokerage (identified by a betweenness centrality measurement) and

a hub (identified by a degree centrality measurement).

From a public relations standpoint, the concept of centrality is most relevant. This importance

stems from the idea that an individual who is close to an actor will have more access to infor-

mation (Leavitt, 1951; Stephenson & Zelen 1989), have more power (Coleman, 1973), have

greater influence (Friedkin, 1991), have higher status (Hubbell, 1965; Katz, 1953) or have great-

er prestige (Burt, 1982) than others in that actor’s network. The two types of structural positions,

as explained next, define centrality, and therefore proximity, differently.

Bridges and Structural Holes

Burt’s (1992, 2001) theory of structural holes examines social actors (e.g., individuals and orga-

nizations) in unique positions in a social network, where they connect other actors that otherwise

would be much less connected, if at all. In Burt’s (2005, p. 24) words, ‘‘A bridge is a (strong or

weak) relationship for which there is no effective indirect connection through third parties. In

other words, a bridge is a relationship that spans a structural hole.’’ A lack of relationships

among social actors, or groups of actors, in a network gives those positioned in previously struc-

tural holes strategic benefits, such as control, access to novel information, and resource broker-

age (Burt, 1992, 2000, 2001). Actors that fill structural holes are viewed as attractive relationship

partners precisely because of their structural position and related advantages (Burt, 1992, 2001).

These actors are called brokers (as they fill a brokerage position) or bridges. These actors form

nonredundant, often weak, ties among otherwise less connected actors (Granovetter, 1973).

To use a contemporary example, Jon may have a group of Facebook college friends, with

whom he has strong relationships. He may also have a relationship with Jamie, whom he briefly

met during an internship in a large PR firm abroad. For Jon’s friends, Jon’s weak relationship

with Jamie may be an important network path to a group of PR professionals abroad. It is also

a nonredundant relationship, as others in his strong and immediate social networks, although

highly interconnected with one another, are not connected to this group of PR professionals.

Jon, then, is located in a powerful structural position in his networks as a broker or a bridge.

This example demonstrates that weak ties often provide less redundant connections—or, in

other words, relationships with people that one’s friends are not connected to. Such nonredun-

dant weak connections are beneficial to individuals, as they gain information not available

through their other social ties, such as solutions for problems, employment opportunities, etc.

These ties are also advantageous because one’s friends depend on that individual for this type

of novel information (Granovetter, 1973).

In the context of mediated public relations, a user filling structural holes (hereafter, a bridge

or a broker) can most appropriately be conceptualized as mediators. As discussed earlier, social

media users (i.e., an audience) that an organization forms direct relationships with often form a

cluster. Relationships with audiences in other clusters are therefore mediated, as an organization

doesn’t reach them directly. Actors located in bridging positions are therefore conceptualized

here as social mediators.

The value of bridges can also be expressed in terms of social capital. Recently, scholars have

argued for the integration of the social capital theoretical perspective in public relations research

(Ihlen, 2005; Pompper, 2012; Sommerfeldt & Kent, 2012). As defined by Kennan and Hazleton

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(2006), social capital is ‘‘the ability that organizations have of creating, maintaining, and using

relationships to achieve desirable organizational goals’’ (p. 322). Due on their role as interme-

diaries in organizational–stakeholder relational outcomes, social mediators intrinsically poses

social capital. One could also argue that social mediators are required to the macro level

organization’s social capital on the Internet. As such, the social network perspective is key to

mapping and identifying social mediators as central players in 21st-century public relations.

Bridges in Directed Networks

Relationships in networks often have a direction. On Twitter, for example, actor A may follow

actor B, but B may not follow A. A bridge, therefore, can be one-way to either direction or

two-way, depending on the direction of relationships with others in the network. Its function

depends not only on its connectedness, but also on the directionality of its connections. Litera-

ture about structural holes, however, has traditionally assumed full symmetry of relationships in

a network (Freeman, 1977).

Conceptually, however, although the directionality of the network affects the function of bro-

kers in the network, the literature about structural holes suggests that they typically assume sym-

metrical relationships. For illustration, one of the core works in the area, Burt’s (2005) book

Brokerage and Closure, reviews a wide range of networks, actors, and relationships, but concep-tually it does not explore the idea that the flow of information through a bridge and the role of a

broker can be defined by the direction of relationships or links in the network. For illustration,

Burt (2005, p. 50) discussed ‘‘kinds of relationships’’ in the context of structural holes, but the

directionality of ties (symmetric or asymmetric) is not addressed.

A closer read of this core literature, however, reveals limited conceptual foundation for

bridges in directed networks. Reviewing and meta-analyzing studies about the spread of ideas,

Burt (2005) addressed the direction in terms of the strength of relationships: no contact, indirect

contact, asymmetric direct contact, and mutual direct contact. He showed an association between

strength of discussion contact and contagion of ideas, particularly for groups of individuals who

have some friends in common, but more that are different (weakly-equivalent people). The most

relevant for this discussion is the reference to Roger’s (1995) idea of opinion leaders. Burt

(2005) refined the definition of an opinion leader as an opinion broker among weakly-equivalent

people. Such individuals are active within their own social groups, but influence those in adjac-

ent groups. One can conclude, then, that connections via mutual connections (i.e., two-way) are

more likely to facilitate spread of ideas than one-way connections. From a public relations theory

standpoint, one can expect that bilateral or symmetric relations of public relations mediators will

be more successful in spreading ideas.

There are also novel attempts to calculate the strength of bridges (i.e., betweenness centrality

measurements) that take into consideration the direction of relationships (e.g., Freeman, Bor-

gatti, & White, 1991; Gould, 1987) but remain under development (van den Brink & Gilles,

2000). These measurements go beyond the traditional binary approach to networks, by including

the directionality of relationships in the calculation. One-way relationships, broadly speaking,

contribute less to an actor’s bridging power than two-way relationships. Such approaches are

important and valuable; however, they do not allow interpreting the values in terms of the

direction of flow. Another network position, which will take into consideration the direction

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of relationships, is therefore required to complete the conceptualization of mediators in public

relations networks.

Hubs

A common role that a social actor may take in social networks is a hub. A hub is an actor with

relationships with many other actors in the network. In social networks terminology, this hub is

essential, as it is high in degree centrality (Freeman, 1977; Wasserman & Faust, 1999). On

Twitter, relationships have a direction (e.g., one user follows another). Two types of degree

centrality, therefore, emerge. In-degree centrality is based on ties or relationships that others

have initiated with a user (e.g., number of users who followed that user). Out-degree is based

on the relationships one has initiated with others (e.g., number of users that a user follows).

From a public relations standpoint, then, organizations that cannot reach users in other clus-

ters are dependent on users who not only bridge users, but also have many relationships directed

to them. Mediators are, therefore, conceptualized here as bridges with high in-degree centrality.

We call them bridging hubs.On Twitter, a bridging hub not only connects an organization with audiences with which it

cannot form direct relations. It also has a large number of users who follow it, as information

it posts about the organization is spread to all its followers. A bridging hub on Twitter is,

therefore, defined as a user that is central both in terms of bridging (measured by betweenness

centrality) and in terms of followers (measured by in-degree centrality; all measures will be

explained in the Methods section next).

Bilateral and Unilateral Relationships as Extent of Reciprocity

On Twitter, relationships have a direction. John may follow Jane, without Jane following John.

The connectivity of a user and its degree centrality has two dimensions. These are its in-ties, or

the number of users following that user (in-degree), and its out-ties, or the number of users it

follows (out-degree). Influential organizations will often have many followers on Twitter; how-

ever, building a relationship with various audiences calls for symmetry (Karlberg, 1996). An

organization’s ratio of followers over following, then, is a more accurate indicator of

relationship-building.

A CASE STUDY: TWITTER AS A PUBLIC RELATIONS TOOL FORTHE US STATE DEPARTMENT

As nations get involved in managing international issues based on strategic perspectives (Kiousis

& Wu, 2008; Wang & Chang, 2004; J. Zhang & Cameron, 2003), social media has come to be

considered critical by governments for strategic public diplomacy (Wanta, Golan, & Lee, 2004).

Several scholars have examined governments’ strategic applications of the US State Department

and explored social media platforms such as Twitter, Facebook, and YouTube as key tools for

international engagement (Hanson, 2012) and for relationship-building between governments or

nongovernmental organizations (NGOs) and foreign publics (Cull, 2008; Leonard, 2002;

PUBLIC RELATIONS ON TWITTER 367

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Leonard & Alakeson, 2000; Leonard, Stead & Smewing, 2002). Given that the objectives and

practices of public diplomacy and public relations share a mutual focus on relationship

cultivation through two-way communication or dialogic communication (Fitzpatrick, 2007;

L’Etang, 1996; Signitzer & Coombs, 1992; Signitzer & Wasmer, 2006; Wang, 2006; Yun,

2006, 2008), national governments’ social media use for public diplomacy can also be valuable

for the public relations perspective.

Twitter has received unique attention from national governments. As a strategic management

platform, Twitter enables governments to freely interact with their foreign publics whenever and

wherever they want. In addition, Twitter has already shown its international influence, from the

2008 US. presidential election (A. Smith, 2009; Zhang, Johnson, Seltzer, & Bichard, 2010) to

the Arab Spring protest movement that reshaped Middle Eastern politics (Burns & Eltham,

2009; Starbird & Palen, 2012). Scholars have also examined how national governments make

use of Twitter, and investigated the critical role of Twitter for relationship management (B.

G. Smith, 2010; Wigand, 2010). However, there is little understanding about how a national

government and its foreign publics communicate by different social mediators on Twitter.

Studying an international social network and discovering social mediators at a macro level

can give governments fundamental guidelines about how to use dialogic communication for

relationship cultivation with foreign publics. Therefore, we applied our conceptualization of

mediated public relations to the social structure of the US State Department’s Twitter account.

In the case of the US State Department, formal social mediators may include government

agencies, whereas informal social mediators may include individuals, NGOs, or other groups.

Unilateral social mediators would be traditional mass media outlets, and bilateral social media-

tors could be nonmass media, including individuals, NGOs, or other organizations. To explore

these influential social mediators, we proposed these research questions:

R1: What are the primarily types of bridging hubs (traditional mass media outlets, individuals,

NGOs, other organizations) followed by users who tweeted about #SecClinton?

Any user—individual, media, nonprofit organization, or government agency, for example—can potentially become a hub on Twitter. Understanding the types of user hubs that appear

together in a cluster can also inform us about the mediated relations between the US State

Department and the publics it does not reach directly.

R2: What types of bridging hubs appear together in clusters?

Addressing a current pressing matter of US foreign relations, particularly in the Middle East,

we also ask:

R3: Are there regional differences in terms of the composition of bridging hubs in clusters?

Based on previous examinations of public relations on social media, and mediated public

relations in particular, key actors are expected to form and maintain bilateral relations with their

audiences. Often, organizations will have many followers on Twitter, as they are well known

beyond the realm of social media. Building a relationship with audiences, however, calls for

symmetry (Karlberg, 1996). Bilateral relationships are also core aspect of social networks. A

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relationship between two actors is reciprocal, or bilateral, if each actor has initiated a tie with the

other actor. On Twitter, for example, a reciprocal or mutual relationship between two users can

be established if they follow one another. The bilateral relationship of an organization with its

audiences on Twitter can, therefore, be conceptualized as the level of reciprocity it has with users

with whom it initiated relationships. Thus, on Twitter, an organization’s symmetry of relation-

ships with its audiences can be conceptualized as the level of reciprocity it has with all users with

whom it has established a relationship and the users who established a relationship with that

organization.

RQ4a: How reciprocal are the relationships between the US State Department and its public?

Although this study primarily focuses on the Department of State, for the broader understand-

ing of symmetry of organization relations on Twitter, the next research question focuses on the

primary actors in the network, the bridging hubs.

RQ4b: Are different types of bridging hubs users different in terms of their reciprocity?

METHODS

This study integrates social network analysis of user-interaction on Twitter with content analysis

of user descriptions. Network analysis is the analysis of patterns of interactions among social

actors, such as individuals and organizations. In this study, social actors include any Twitter user

who tweeted using the hashtag #SecClinton. This includes individuals, government agencies,

and media. Relationships were created when users followed, replied or mentioned one another.

Next, we describe the data collected, as well as the types of analysis applied.

Data

Twitter usernames, user statistics (e.g., profile description and URL, number of followers), user

images, and follow relationships were collected, and we identified user-posted comments

associated with the US State Department by using the hashtag #SecClinton. We selected this

specific hashtag after evaluating data collected for other State Department-related hashtags

(i.e.,#StateDept,#SecClinton). The results of the preliminary analysis showed that#StateDept

s not frequently used and therefore #SecClinton was selected for this study. We collected data

using NodeXL’s Twitter Search importer (Hansen, Shneiderman, & Smith, 2011), which ident-

ifies Twitter users who included the hashtag. Hashtags create topic networks, and so

#SecClinton creates a specific network with the secretary of state as the topic. It should be noted

that tweets that included #StateDept, the State Department’s hashtag, were first collected.

However, it led to insufficient datasets that were not appropriate for analysis. We performed

10 data draws, every Wednesday and Monday, between November 17, 2011 and December

19, 2011. Each dataset was limited to 1,000 users and their relevant tweets, as the Twitter

Application Programming Interface limits the amount of content that can be downloaded.

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Measurements

Network analysis. The clusters in the topic-networks were identified using the Clauset–

Newman–Moore algorithm (Clauset, Newman & Moore, 2004). The density of each cluster

was calculated as the number of existing following relationships among Twitter users within

a given cluster divided by the total possible number of relationships among those same nodes.

Identifying bridging hubs. Each topic-network consists of nodes and following relationships

(directed ties). We propose here to operationalize Twitter bridging hubs as users who are at the top

2.5% in the network in terms in-degrees centrality values and the top 10% in terms of betweenness

centrality. This operationalization gives priority to in-degree as it ensures the direction of infor-

mation flow toward the public. Betweenness centrality measures the extent that the actor falls

on the shortest path between other pairs of actors in the network. The more people depend on

an actor to make connections with other people, the higher that actor’s betweenness centrality value

becomes. This value is, therefore, associated with bridging actors in a network. However, between-

ness centrality measures do not take into consideration the direction of relationships. As directors of

information flow from an organization to audiences in a social network, the mediated user should

not only connect, but also attract large audiences. The second aspect of the operationalization of

bridging hubs should therefore be high in-degree centrality. In-degree centrality is measured as

the number of followers a user has among the other members of the specific topic-network. Twitter

hubs account for a significant amount of information flow through the Twitter networks due to the

expected, severe skew on distribution of Twitter followers (Raban & Rabin, 2007).

Content analysis. We classified Twitter users into types of information sources identified

using content analysis. Specifically, two researchers worked together to develop a codebook

based on a preliminary analysis of all users in the first two datasets. We identified five primary

sources: foreign governments, US governments, mass media, NGOs and individuals. Each

source was also classified, where possible, by its geographic location: Asia, East Asia, Europe,

Middle East and North Africa, North America, Oceania, South America, South Asia, and

sub-Saharan Africa. Self-identified geographic location was cross-referenced, where available,

with data available via hyperlinks in the accounts’ profiles. When these two methods did not

lead to a clear geographic location, a Google search was conducted using the username as a key-

word. For 3.1% of the hubs, the coders could not identify the geographic location.

Findings

At 10 points throughout the study, actors using the hashtag #SecClinton were collected and

recorded for research. In each dataset, the top 2.5% of users, determined by their positions in

their respective issue-networks, were identified as bridging hubs (hereby, hubs; N¼ 1180).

R1: What are the primarily types of bridging hubs (traditional mass media outlets,individuals, NGOs, other organizations) followed by users who tweeted about#SecClinton?. Users affiliated with the US government make up about half of the hubs

(n¼ 559, 47.4%). The second most popular hubs are associated with individual users, not

affiliated with any major governmental, media-related, or other institution (n¼ 319, 27.0%).

NGOs represented 14.7% (n¼ 174) of the hubs. News media, a natural target of governmental

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communication, only represented 8.0% (n¼ 94). Finally, foreign governments accounted for

2.9% of the hubs (n¼ 34). See Figure 1 for details.

R2: What types of bridging hubs appear together in clusters?. Taking a social network

approach to examining communication on Twitter about #SecClinton, we applied a clustering

algorithm to identify network clusters. This procedure identifies subsets of users (i.e., clusters)

who interact primarily with one another in comparison to interactions with users in other subsets.

For each cluster, the number of bridging hubs was calculated according to their specific types.

This resulted in a description of the major subgroups of users (who followed, mentioned, and

replied to one another) and the major mediator (i.e., bridging hubs) in each one, connecting them

to users in other clusters.

We applied a factor analysis to identify the types of hubs that tend to appear together in clus-

ters of users. A factor analysis with a Promax Rotation resulted in two components, accounting

for 60.03% of variance. To increase explained variance (78.76), a three-component solution was

forced, resulting in the following components: (a) NGOs (e.g.: Oxfam America @oxfamamer-

ica), individuals (e.g., Terri Harvey @terri georgia) and foreign governments (e.g., Netherlands

Embassy @DutchEmbassyDC), (b) the US government (e.g., Americagov @americagov), and

(c) media (e.g., The Washington Post @washingtonpost). Cross-loadings were primarily low.

It should be noted that although foreign government accounts appeared in the first components

(grassroots), it accounted for only 3% of the bridging hubs and therefore is not a meaningful

category in that component. One medium size negative cross-loading (�.348) was found for

individual hubs with the US government components. See Table 1.

RQ3: Are there regional differences in terms of the composition of bridging hubs inclusters?. Only 8.4% of the hubs were associated with Middle Eastern and North African

countries (n¼ 99). About half of the hubs (n¼ 613, 51.9%) were associated with North America

(primarily the United States). Next, 16.9% were associated with European countries (n¼ 199).

The remainder was associated with East Asia (6.9%), South Asia (6.0%), Oceania (3.6%), South

America (1.7%) and the sub-Saharan counties (1.0%). For 36 hubs (3.1%), all associated with

individual users, we could not identify a geographic location.

FIGURE 1 Hubs by type of source (N¼ 1180).

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The most interesting finding here is the prevalence of individual hubs in the Middle East. In

every other area, hubs associated with the US government were the majority, and were often the

only hubs. Of a total of 99 hubs identified as being located within Middle East and North Africa

(MENA) countries, 62 were associated with individuals and only 29 with the US government.

Notably, NGOs were not dominant in any particular geographic area. NGOs appeared the most

in North America, primarily the United States. See Figure 2 for more details.

These findings were complemented by a factor analysis performed using a cluster as a unit of

analysis. The procedure resulted in two components (61.47% explained variance): one associa-

ted with MENA and the second with all other geographic regions. The dominance of US govern-

ment hubs in all regions but MENA can explain the resulting components. Forcing a larger

number of components to increase explained variance did not change the original results point-

ing out MENA hubs as a distinct component. See loadings in Table 2.

RQ4a: How reciprocal are the relationships between the US State Department and itspublic?. User’s reciprocity, as discussed earlier, is measured as the portion of reciprocated

relationships of the total number of relationships it has with others in the network. Reciprocity,

TABLE 1

Factor Analysis Loadings (Forced Three Components)

Grassroots component Media component US Government component

Government—Foreign .930 �.262 .079

Government—US .028 .008 .962

Individual .648 .100 �.348

Media �.090 .979 �.011

Nongovermental organization .650 .350 .174

FIGURE 2 Type of hubs by geographic location.

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then, can vary across time. On one week, for example, the State Department can be more

involved in the conversation, replying to those who use the hashtag and mentioning other users

in their tweets, than on other weeks. Over the 10 points of data collection, 10 reciprocity values

TABLE 2

Factor Analysis Loadings

Component 1 Component 2

Asia .601 .150

East Asia .342 �.770

Europe .702 .028

MENA� .117 .657

North America .780 .192

Oceania .796 �.264

South America .822 .109

South Asia .950 �.118

�MENA¼Middle East and North Africa.

FIGURE 3 The Social Network of the #SecClinton Twitter Talk (11-28-2011)�. �This network maps the relationships

among Twitter users who posted messages using the hashtag #SecClinton on 11-28-2012. The network illustrates the

clusters, sub communities of interconnected users. On the left, users with which the State Department has direct relation-

ships. In the center-bottom, the MENA oriented cluster, includes bridging hubs from the region. On the top-center, the

cluster is dominated by individuals and bloggers. On the left-right, a cluster surrounding U.S. agencies around the world.

The relationships across clusters illustrate mediated public relations. Bridging hubs in the various clusters are connected

(follow) the State Department’s Twitter account.

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were calculated: M¼ .08, SD¼ .06. The distribution was not normal, as at two points of time

reciprocity was high (.22 and .25) and in the rest, much lower (.03 to .08).

RQ4b: Are different types of bridging hubs users different in terms of theirreciprocity?. Overall, reciprocity between bridging hubs and their audiences showed a mean

of .17 (SD¼ .09). Controlling for date of data collection, a regression analysis was applied to

examine a relationships between type of bridging hubs and reciprocity. Individuals exhibited

the highest reciprocity values (M¼ .19, SD¼ .11), closely followed by foreign governments

(M¼ .18, SD¼ .11), US government agencies (M¼ .17, SD¼ .78) and NGOs (M¼ .16,

SD¼ .08). The lowest reciprocity levels were exhibited by media (M¼ .12, SD¼ .09). Relation-

ship was significant (p< .01), but the effect size was rather low (adjusted R2¼ .08). This may be

a result of the little differences among all categories except media. Indeed, a post-hoc regression

analysis, controlling for date and using only two values of users—media and non-media—led to

significant (p< .001) and stronger results, in terms of adjusted R2 (.29).

Figure 3 illustrates the process of mediated public relations on Twitter. Users form clusters—interconnected subgroups of users—surrounding sets of bridging hubs. For example, on the left

is a cluster associated primarily with the Twitter account of the State Department. The agency

has direct relationships with users in this cluster. As the star-shape structure indicates, these users

follow the U.S. State Department account. On the bottom-center, one can find a cluster sur-

rounding local grassroots Twitter-hubs, such as Anmar Kamalaldin (@anmarek), who describes

himself as a Bahraini Citizen Seeking Freedom & Democracy (not a member of any political

party), or the activist @iProtestor from Bahrain. At the top-center, one can find a cluster sur-

rounding primarily activists, such as the actress Mia Farrow and Cameron Sinclair, the cofoun-

der of Architecture for Humanity. The ties across the clusters illustrate mediated public relations,

as bridging hubs follow the US State Department’s Twitter account.

DISCUSSION

This study proposed a strategic, conceptual framework to identify social mediators and to use the

social network approach to explicate and investigate mediated public relations efforts on social

networking sites. This approach is highly appropriate to studying originations–stakeholder rela-

tionships at the macro level, as called for by scholars (Rowley, 1997; Sommerfeldt, Kent, &

Taylor, 2012). Mediated public relations was characterized by social mediators’ functional fea-

tures (formal and informal) and interdependent connections (unilateral and bilateral). We then

applied the framework to conduct a social network analysis that explored how the US State

Department and its foreign publics are reached by social mediators, including individuals,

NGOs, governmental agencies, and mass media on Twitter.

Findings inform us about two key aspects regarding public relations. First, we identified for-

mal and informal mediators that bridge the State Department with audiences the agency does not

interact with directly. Just under half of all mediators were formal actors, primarily US govern-

ment agencies at home and around the world. A similar portion of mediators were identified as

informal mediators, composted by individual activists and NGOs. Media outlets, traditional and

formal actors in public relations, accounted only for less than 10% of social mediators in this

study. Notably, formal social mediators, such as US agencies, were pervasive across most of

the regions identified in this study, with the exception of one key region: the Middle East

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and North Africa. Relationships with stakeholders in this region were mediated by informal

mediators, which the State Department has no direct control over.

A second public relations concept that was examined here is bilateral relationships in

mediated public relations. On average, US agencies, including the State Department, performed

as well as less formal mediators. Media mediators were the primary exception, with much lower

measures of reciprocity. The results of our study identify that, on average, the State Department

and US agency relationships with their stakeholders were unilateral, rather than bilateral. Com-

parably, media relationships were more unilateral, indicating that US agency relationships on

Twitter trend toward a broadcast, rather than a two-way communication, model.

This study extends the understanding of social media, particularly social networking sites, as

it provides a valuable framework of mediated public relations. In comparison with prior research

studies discussing mediated relationships that mainly focus on types of media (Kent & Taylor,

2002), we expanded the notion of mediated public relations by focusing on social mediators of

micro-blogging. Recognizing the need to move beyond the narrow OPR approach (Edwards,

2012), our study examines the interaction between organizations, stakeholders, and social media

mediators. Our results point to a multidimensional interaction between the organization (US

Department of State) formal (government, media) and informal mediators (individual users)

and target stakeholders (foreign publics) that collectively paint a more complete picture of the

complex nature of public relations in the social sphere. Public relations scholarship, therefore,

must recognize the potential impact of social mediators; given that even an individual can func-

tion as a powerful media source on social networking sites, it is critical to focus on understand-

ing the unique characteristics of social mediators. In addition, as some scholars have pointed out,

even nonpublic-relations entities may participate in public relations activities (Kelleher, 2009; B.

G. Smith, 2010). Therefore, social mediators can play a significant public relations role in a

social network. It implies that the role of public relations can be extended to social mediators

if one considers them as collaborators located outside of an organization. In particular, a microboundary spanning role can be regarded as one potential function, which social mediators can

adopt through social media.

Our study also provides practical guidelines for public relations practitioners in charge of

public diplomacy. Through Twitter, the US State Department and its publics were mediated

more by formal social mediators such as government agencies, than by informal social mediators

such as individuals and NGOs. Also of note is that informal mediators were more influential than

formal ones only for the Middle East and North Africa. This suggests that there is a possibility to

strengthen nongovernmental policy, but it must be strategically executed, as there is less control

over distributing governmental information through social media.

Last, this study makes interesting observations regarding the most traditional public relations

mediators: mass media. First and foremost, mass media actors composed less than 3% of the

mediators in this study. Second, mass media still represents unilateral interactions even on social

networking sites such as Twitter. Many scholars have examinedwhy some organizations fail to make

an effective use of social media (J. E. Grunig, 2009; Sweetser, 2010; Waters et al., 2009). We found

that social mediators such as individuals, NGOs, and other organizations were more likely to be

bilateral than mass media in terms of making relational ties. It implies that the US government

should not underestimate nonmass media as key mediators for relationship cultivation.

Our study also makes a methodological contribution to the field of public relations in terms of

data collection, analysis, and mapping of OPRs. Sedereviciute and Valentini (2011) posited that

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organizations are not fully aware of their key stakeholders in the social sphere. Similarly, Barley,

Freeman, and Hybels (1992) suggested that it is through the examination of an overall network

that an organization can fully understand the potential of organizational opportunities. This claim

was tested and supported by Taylor and Doerfel (2003). The use of network analysis and the

NodeXL software give public relations scholars and practitioners access to data collection,

analysis and visualization. This toolkit can provide organizations with the ability to map, track

and evaluate their relationships from a macro perspective.

A potential key limitation for this study is related to the Smith-Mundt Act, which restricted the

distribution of foreign targeted media content from the Broadcast Board of Governors (BBG)

communication channels to domestic publics in the United States. Although this study did not

examine BBG-specific content (such as the Twitter accounts of Voice of America, BBG, or

Radio), restrictions from the Smith-Mundt Act may have limited the overall body of content from

which #SecClinton Twitter data was collected. Indeed, the Department of State stated that

‘‘Department-generated Public Diplomacy content must be carefully reviewed to avoid

violations’’ of this act (US Department of State, 2011, p. 11). We acknowledge this potential

limitation for our data, as it was collected before the amendment of the act, which now allows

domestic distribution of BBG content under the National Defense Autorotation Act 2013. The

rich data collected here and the overall positive approach of the Department toward the use of

social media ‘‘encourages the responsible use of social media consistent with current laws,

policies and guidance’’ (US Department of State, 2010, p. 5). However, we believe that the data

and findings are meaningful. That said, concerns were raised regarding the Department’s blog,

DipNote, where personal information and geographic locations could not be confirmed.

Therefore, one may inadvertently violate the limitations of the Smith-Mundt Act regarding the

domestic distribution of information. This led to a limited amount of dialogue with users. Recip-

rocity is, therefore, the measurement that would be most affected by such limitations. However,

findings suggest that reciprocity measurements of US agencies’ bridges, including the State

Department, were only slightly lower than of individuals, who are not restricted by the act.

Another possible limitation is the anonymous nature of social media and the Internet in general.

An individual who may be concerned with being targeted by an authoritarian regime, for example,

may post misleading information about themselves. The low number of Twitter users in theMiddle

East identified in this study, then, may potentially be much higher. This anonymous nature of the

Internet somewhat undermines almost any analysis of user-generated and self-reposted content.

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