Sharing Knowledge and “Microbubbles”: Epistemic Communities and Insularity in US Political Journalism


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DOI: 10.1177/2056305120926639
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Original Article

Though a critique of “Eastern Liberal Media” generally dates 
to Barry Goldwater in the 1960s (Hemmer, 2016), the accu-
sations in the United States against the “elite media” and 
“coastal elitism” have reached a fever pitch in the Trump era. 
Journalists widely predicted that Hillary Clinton would win 
the 2016 election. The aftermath prompted renewed interest 
among journalists and scholars focused on the United States 
as to whether political journalists, particularly those in 
Washington, were in a “media bubble.” In fact, Benkler et al. 
(2018) found that journalists on Twitter had almost no expo-
sure to Trump supporters. US journalists are more likely to 
be insulated in liberal political bubbles in big cities that are 
growing “bluer” (Shafer & Doherty, 2017). In Washington, 
often referred to as “the Beltway,” journalists are overrepre-
sented at 10 times the density and are paid more than any-
where else in the United States (Bureau of Labor Statistics, 
2018). Normatively, there is reason to be concerned that 
insularity leads to blind spots, perhaps worsening what Frank 
(2003) calls “intrusive reporting and excessive coverage” in 
“the face of public disaffection” (p. 441).

However, scholarly research on elitism and insularity in 
political communication tends to be largely theoretical 
(e.g., Bennett, 1990; Entman, 2004; Scheufele, 1999), 
descriptive at small scale (Bennett et al., 2008; Davis, 
2002), and often demonstrated via content analysis (e.g., 
Dunaway & Lawrence, 2015; Zhou & Moy, 2007), rather 

than as explanatory accounts of work routines, knowledge 
production, and sense-making. New research that uses 
Twitter data augments these insights (e.g., Freelon & Karpf, 
2015; McGregor & Molyneux, 2018; Molyneux & Mourão, 
2019), though this work tends to be functionalist, focusing 
on how practices are normalized into work routines, leav-
ing critiques of power on the periphery.

Given the current context of record distrust in news media 
both in the United States and abroad (Pew Research Center, 
2018), the case for a contemporary inquiry into the “power 
elite” (Mills, 1959), and more specifically, what S. Lichter 
et al. (1986) called the “media elite” is warranted. Of particu-
lar interest is the knowledge-generation and sense-making 
processes in the “Beltway bubble.” In this article, we focus 
on US political journalists’ interactions among themselves, 
rather than their role in larger system of information flows. 
We apply research on Communities of Practice (CoPs), and 
the closely related concept of epistemic culture, widely 
established in management and sociology research (Knorr 
Cetina, 1999; Lave & Wenger, 1991), to understand the 

926639 SMSXXX10.1177/2056305120926639Social Media <span class="symbol" cstyle="Mathematical">+</span> SocietyUsher and Ng
research-article20202020

University of Illinois at Urbana–Champaign, USA

Corresponding Author:
Nikki Usher, College of Media, University of Illinois at Urbana–
Champaign, Urbana, IL 61820, USA. 
Email: nusher@illinois.edu

Sharing Knowledge and “Microbubbles”: 
Epistemic Communities and Insularity in 
US Political Journalism

Nikki Usher  and Yee Man Margaret Ng

Abstract
This article examines the peer-to-peer dynamics of Washington political journalists as Communities of Practice (CoPs) 
to better understand how journalists connect to and learn from each other and establish conventional knowledge. We 
employ inductive computational analysis that combines social network analysis of journalists’ Twitter interactions with 
a qualitative, thematic analysis of journalists’ work histories, organizational affiliations, and self-descriptions to identify 
nine major clusters of Beltway journalists. Among these are an elite/legacy community, a television producer community 
inclusive of Fox producers, and CNN, as its own self-referential community. Findings suggest Washington journalists may be 
operating in even smaller, more insular microbubbles than previously thought, raising additional concerns about vulnerability 
to groupthink and blind spots.

Keywords
media elites, political journalism, Communities of Practice, epistemic communities, Twitter, social network analysis

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2 Social Media + Society

mechanisms through which political journalists engage with 
each other to develop shared practices and knowledge. CoP 
research has often been used in the context of social learning 
with the aim to improve how knowledge and resources can 
be shared within and across organizations (Brown & Duguid, 
1991; Mørk et al., 2008). When epistemic cultures become 
fragmented or closed, the consequences can be catastrophic, 
from space shuttle disasters (Vaughan, 1996) to disruptions 
in global financial markets (Knorr Cetina & Preda, 2005). 
How political journalists make sense of what news to cover 
and how to cover it, particularly as peers across news organi-
zations, stands to shed insight into the contours of the insu-
larity long observed in political communication scholarship 
(Harcup & O’Neill, 2017).

We employ an inductive computational approach that seeks 
to bridge qualitative inductive approaches with big data (Usher, 
in press) to examine a purposive sample of 2,506 Beltway jour-
nalists. We conducted a social network analysis of 133,529 
tweets along with analyses of word clouds, biographical, and 
employment data. Empirically, we find that Beltway journal-
ism should not be generalized as a monolith, and instead should 
be understood as multiple CoPs tied together by distinct types 
of shared knowledge practices, norms, and routines. In short, 
the Beltway’s “media bubble” looks more like a collection of 
“micro bubbles,” suggesting Beltway journalism may be even 
more insular than previously thought.

CoPs and Epistemic Culture

Zelizer’s (1993) theoretical insight that journalists form 
“interpretive communities” is fundamental to discussions 
about in-group identity formation, claims to cultural author-
ity and institutional legitimation, and the ways in which jour-
nalists mediate events. Metajournalistic discourse, a closely 
related concept, reflects how journalists and those interested 
in journalism engage in a process of critique and reflexivity 
about journalistic practice (Carlson, 2015). The CoP 
approach extends these concepts focusing on what Mørk 
et al. (2008) identify as “the relationship between practice, 
learning and innovating” (p. 13). This is intentional, as CoPs 
help reveal why knowledge production and transfer stalls, 
why openness to innovation and new ideas breaks down, and 
what facilitates building networks of intra- and cross-organi-
zational knowledge (Orlikowski, 2002; Wenger, 1998).

Moreover, considering epistemic cultures within CoPs 
reveals what Knorr Cetina (1981, 1999) calls “machineries 
of knowledge production”—that knowledge cultures are 
mechanistic, produced through, and constituted by practice. 
CoPs are based on mutual engagement that brings together 
actors of different abilities bound by a “shared repertoire of 
communal resources (routines, sensibilities, artifacts, vocab-
ulary, styles, etc.) that members have developed over time” 
(Wenger, 1998, p. 98). Members involved are presumed to 
engage in shared goals or beliefs and have a sense of joint 
enterprise and identity (Wenger, 1998).1

As such, these concepts help us think more generally 
about how journalists come to know about particular sub-
jects, who they engage with, and help us uncover tacit under-
standings of purpose, practice, and identity. In a 2005 
collection, The Practice Turn in Contemporary Theory, 
Knorr Cetina et al. (2005) bring scholars together to think 
about the connection between practice, power, and knowl-
edge. Schatzki (2005) offers a general gloss on “practice” as 
a form of non-regularized knowledge organized by practical 
understandings and rules. The connection between shared 
practices and knowledge generation has distinct power 
dynamics; as Barnes (2005) explains, “to engage in practice 
is to exercise a power . . .” (p. 28).

In addition, Fox (2000) argues that CoPs are also subject 
to peer-established disciplinary forces.

Indeed, Knorr Cetina’s (1981, 1999) closely related con-
cept of epistemic culture (a.k.a., epistemic communities) 
suggests devastating consequences for insular CoPs filled 
with elites. Knorr Cetina (2007) argues that epistemic cul-
tures emerge “when domains of social life become separated 
from one another—when they curl up upon themselves,” 
which in turn suggests “rich and potentially complex internal 
environments with warped geometries” (p. 364). Amin and 
Roberts (2008) characterize epistemic communities as char-
acterized by “collaborations involving experts with substan-
tial egos, high expectations, frequent turnover, rudimentary 
rules and procedures, tight deadlines, and considerable ambi-
guity and uncertainty” (p. 361).

Knorr Cetina’s research on high-frequency traders has 
many parallels to Beltway journalism. These traders see 
themselves as engaged in specialized knowledge production 
and are constrained by tacit and explicit norms that limit 
input from outsiders. Similarly, their peer-to-peer relation-
ships are distributed across loose networks, facilitated via 
Internet communication technologies. Shared sense-making 
and knowledge production becomes increasingly important 
as traders work faster and faster with diminished opportuni-
ties for independent research. Imbued with a sense of power, 
privilege, and invulnerability, the more insular and confident 
these “masters of the universe” (Wolfe, 1987) become, the 
harder they can fall.

Existing research on CoPs and epistemic culture in jour-
nalism is sparse. However, this is a missed opportunity; CoPs 
complement the findings of early newsroom ethnographers 
(Gans, 1979; Tuchman, 1978), who examined how the 
knowledge production process was influenced by actors 
inside and outside journalism who ordered practices of 
knowing. More recently, García-Avilés (2014) discussed 
how online newsrooms constituted CoPs, while Borden 
(2007) used CoPs to explore the tacit understandings of jour-
nalists’ “virtue ethics.” Husband (2005) and Matsaganis and 
Katz (2014) consider how ethnic media operates as CoPs, 
suggesting a rationale for considering other beats/media spe-
cializations. Overall, CoPs are united by a common material 
point of inquiry, object, or concern, but epistemic cultures 



Usher and Ng 3

are vulnerable to collapsing inward, resulting in Knorr 
Cetina’s warped geometries.

Beltway Insularity and Twitter

Political journalists are high-ego actors whose loose connec-
tions to each other are facilitated by instant communication 
(in particular, Twitter). Like most journalists, they are asked 
to do more with less time (Hamby, 2013), which can lead to 
shortcuts and imitation (Boczkowski, 2009). Yet even in a 
hybridized media environment, Washington political jour-
nalists still have outsized power, status, and influence in 
shaping what the public knows about politics. Part of this 
power comes from Washington’s clubby insularity, in which 
national media and political elites engage in a process of 
mutual influence and dependence (cf., Bennett, 1990; Davis, 
2007; Entman, 2004) and drive each other’s agendas as well 
as the public’s (McCombs et al., 2014). The regular and 
ongoing informal socialization and formal professionaliza-
tion, long hours on the job (often in places exclusively desig-
nated for the press), and underlying pressures of competition 
among news organizations can also lead to conformity and 
homogenized coverage (Cook, 1998; Davis, 2007). As 
Bennett (1996) finds, this type of socialization leads “national 
news organizations to the same information sources and, as a 
result, to much the same stories” (p. 373), which in turn can 
“naturalise” the perspectives of powerful elites (Hall, 1973; 
Harcup & O’Neill, 2017).

The consequences of the insularity observed among the 
Beltway elites are significant for the kind of knowledge pro-
duced. Research on pack journalism suggests evidence of 
journalistic “groupthink,” which Matusitz and Breen (2012) 
define as “a consensus-seeking propensity in certain groups” 
(p. 898). They point out the danger of pack journalism, defin-
ing it as “a practice whereby large groups of reporters cluster 
around a news site, engage in copycat reporting by using and 
sharing news information, and lazily refrain from confirming 
the data through independent sources” (p. 898). Similar trends 
have been observed among other elite beats, such as science 
journalism. In 1980, Dunwoody observed how a small “inner 
club” of writers of science journalists who knew each other 
and cooperated over a long period had outsized influence on 
shaping science coverage for US readers (p. 14). Brüggemann 
and Engesser (2014) observed this among contemporary cli-
mate journalists, noting the practice of knowledge sharing 
and production reifies powerful journalists and establishes 
consensus. Moreover, Berkowitz and TerKeurst (1999) sug-
gest a geographic community’s culture and power structure 
can shape news decision-making processes—supporting the 
importance of inquiry into the knowledge-generation prac-
tices of journalists within the Beltway. Similar concerns are 
present where large concentrations of journalists gather to 
cover political power (e.g., the “Brussels Bubble,” 
“Westminster Village,” or Berlin’s “spaceship”; Cornia, 2010; 
Hanusch, 2018; Nielsen, 2014), though political journalism is 

“no one thing, not in the United States and certainly not across 
all of Western Europe” (Nielsen, 2014, p. 172).

Overall, previous research into offline political journal-
ism practices highlights proclivities toward groupthink, insu-
larity, the silencing of divergent perspectives, and limitations 
in knowledge production, suggesting the importance of a 
CoP analysis of Beltway journalism. However, there is a 
paucity of in situ observational research on how political 
journalists work in the contemporary environment (though 
see Davis, 2010; Lawrence, 2015). The classic The Boys on 
the Bus (Crouse, 1973) and more contemporary memoirs by 
journalists (e.g., Chozick, 2018) tell us a bit about the peer-
to-peer knowledge production processes of political journal-
ists. However, academics have distinct challenges to 
accessing these settings, and while not a replacement, explor-
ing peer-to-peer dynamics of journalists on Twitter functions 
as a proxy for observational studies. The ability to observe 
these dynamics at scale through social network analysis pro-
vides a different, possibly more ecologically expansive per-
spective than the fieldwork of a single scholar.

If there is one academic occasion, when it is appropriate 
to say that Twitter is representative of the lived experience of 
the people using it, the case of Beltway journalists would be 
it. For political journalists, Twitter functions as a synchronic, 
digital extension of political journalists’ offline lives as they 
do their work and engage with each other (Kreiss, 2016; 
McGregor & Molyneux, 2018). Twitter serves as a virtual 
“watercooler” (Hamby, 2013); Lawrence (2015) quoted one 
journalist who said, “The people I know who are on Twitter 
are other journalists” (p. 93). In the contemporary agenda-
setting process, journalists and news organizations play an 
outsized role on Twitter and are more influenced by Twitter, 
“indicating processes of monitoring, imitation, and co-orien-
tation between different media outlets” (Harder et al., 2017, 
p. 14). In fact, as McGregor and Molyneux (2018) show via 
an online survey experiment, the more time journalists spend 
on the platform, the more that journalists’ news judgment 
changes to normalize Twitter with more standard forms of 
newsgathering. Of course, this is not to say that journalists 
do not engage in more varied mechanisms for enhancing 
their reporting, editing, and analysis, such as traditional 
sourcing and in-person interviews.

Indeed, the CoPs of journalists that exist offline are thus 
facilitated by Twitter. Journalists tweet to and about other 
political journalists more than they engage with any other 
type of user (Molyneux, 2015; Molyneux & Mourão, 2019); 
Twitter can make or break the reputations of political jour-
nalists jockeying for hierarchy and prestige (Mourão, 2015). 
Twitter is now the primary place to break and spot breaking 
news, to demonstrate humor, snark, and insider knowledge, 
and to be validated by journalism peers (Freelon & Karpf, 
2015; Hamby, 2013; Mourão et al., 2015). Twitter use by 
journalists can also reinforce predominant interpretations of 
ongoing events (Thompson, 2016). In fact, as Jürgens et al. 
(2011) argue, political journalism Twitter has a “small world” 



4 Social Media + Society

effect that is highly influenced by a small number of users 
critically positioned in the structure of the network. Insular 
tendencies and power dynamics observed offline are also 
present, and in some cases, amplified on Twitter, as shown 
by research on gender disparities in Beltway journalism 
(Usher et al., 2018).

McGregor (2019) found that journalists rely on Twitter as 
a standard bearer for public opinion. Still, we do not know as 
much about how journalists use each other, via engagement 
on Twitter, as a site of knowledge generation, despite the sig-
nificant consequences for news production. Thus, to better 
understand how political journalists engage with each other 
as CoPs in an era of Twitterified journalism, we pose the fol-
lowing research questions:

RQ1. What are the peer-to-peer dynamics in political 
journalism?

RQ2. Why might these community dynamics occur?

RQ3. What kind of knowledge is shared by/among politi-
cal journalists?

Method

Data Collection

We identified a purposive sample of journalists who could all 
be described as elite political journalists, drawing from the 
list of 5,783 credentialed congressional correspondents (in 
categories of daily press, periodical press, and radio/TV) 
found in the Congressional Directory for the 114th Congress 
of the United States.2 To be credentialed, a journalist is vet-
ted by The Standing Committee of Correspondents, which 
consists of five journalists elected by their peers. Journalists 
must permanently reside in Washington, DC, work full-time 
as a journalist, and be “editorially independent of any institu-
tion, foundation or interest group that lobbies the federal 
government, or that is not principally a general news organi-
zation” (Congressional Directory, 2016, p. 976). This cre-
dentialing is a requirement for joining the White House 
Correspondents Association, and most news outlets will also 
pro-forma apply to credential their Washington journalists. 
As such, the list is among the most comprehensive of 
Washington journalists.

From this list, we identified journalists with active Twitter 
accounts and updated the list, eliminating journalists who 
were identified as no longer working for a news organization 
or residing in Washington and confined our sample to 
English-language outlets. This list-building process took 
2 months and was completed on May 31, 2017. Though this 
list inevitably changes, it is nonetheless a sample of journal-
ists living and working in Washington who share key mea-
sures of occupational prestige: elite political journalists 
doing work considered worthy of permanent credentials to 
cover Congress.

Our purposive sample started with 2,506 credentialed 
Washington journalists with Twitter accounts. Using 
Twitter’s timeline application programming interface, we 
collected 680,021 tweets posted by 2,292 accounts from 
February 1 to March 31, 2018, a 2-month timeframe that 
gave us both enough data and temporal specificity about sig-
nificant news stories/events, giving us a better sense of the 
content Beltway journalists were talking about with each 
other on Twitter. To set the network boundary, we further 
narrowed our data set to only tweet conversations among the 
Beltway journalists. That included retweets, replies, and 
original tweets where a Beltway journalist directly refer-
enced another Beltway journalist. Excluded tweets were 
those from accounts outsides of our sample that referenced 
Beltway journalists, as well as tweets from Beltway journal-
ists that engaged with accounts other than those journalists 
in our sample. The final data set consisted of 133,529 tweets 
from 2,015 journalists (one-third of all credentialed con-
gressional correspondents). Close to one fifth (19.63%) of 
these tweets were interactions with other Beltway journal-
ists in the sample; if we included not just Beltway journal-
ists, but all the journalists our sample engaged with, extant 
research suggests this percentage would likely be greater 
(Table 1 shows the percentage of in-group tweets within the 
specific communities).

We imported the final data set Gephi (Bastian et al., 2009) 
to visualize the internal patterns of clustering and inter-clus-
ter relations among the Beltway journalists (Figure 1). Ties 
were formed based on three types of relationships, namely, 
mentions, retweets/quote tweets, and replies. A directed tie 
from user A to B was established when user A either men-
tioned user B in an original tweet or when user A retweeted 
or replied to user B’s Twitter posts. In total, there were 
137,620 directed ties (separate ties were drawn when one 
single tweet mentioned or replied to multiple Beltway jour-
nalists). Edges in the network were then “weighted” based 
on the number of ties between two Beltway journalists.3

Inductive Computational Analysis of 
Communities

Our work proceeds through a methodological innovation 
called inductive computational analysis (Usher, in press), 
which helps us address a methodological difficulty: the 
inability to understand at scale the enduring patterns of inter-
action among political journalists. Asking more than 2,000 
Washington journalists, how they engage with peers, who 
they think they talk to the most, and how they use insights 
from others to develop their story frames and ideas is impos-
sible to do given limited resources and still would have the 
limitation of only providing individual perspectives on peer-
to-peer relationships. Observational work is also particularly 
challenging as regular access to spaces within the corridors 
of political power is difficult to obtain. Therefore, the aim of 
inductive computational analysis is to answer questions often 



Usher and Ng 5

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6 Social Media + Society

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Usher and Ng 7

posed by a qualitative researcher by “interviewing” and 
“observing” big data sources instead of (or in addition to) 
interviewing and observing a population of interest.

As we were interested in understanding how CoPs of 
Beltway journalists interact and engage, we applied network 
community detection to identify clusters of journalists that 
have strong within-group connectivity versus between-group 
interactions. One of the pertinent properties in real-world 
social networks is their community structures. Generally, a 
community is defined as a group of nodes (i.e., journalists in 
this study) having similar affiliations different to the rest of 
the network (Yang et al., 2010). Community detection identi-
fies cohesive subgraphs of users that are more densely con-
nected to each other than to the rest of the network 
(Papadopoulos et al., 2012). We specifically used the Louvain 
modularity algorithm (Blondel et al., 2008) to examine the 
community structure, where a zero modularity score repre-
sents randomly connected networks and a score greater than 
.3 infers networks with substantial community structure 
(Newman & Girvan, 2004). This algorithm performs particu-
larly well on large and weighted networks (Blondel et al., 
2008; Lancichinetti & Fortunato, 2009) as well as networks 

based on social media (e.g., Haynes & Perisic, 2009). The 
output of community detection usually results in networks 
with hundreds of identified clusters with many clusters only 
containing a few users; however, little research has provided 
an appropriate cut-off number to analyze clusters (Guo et al., 
2018). As such, we chose to analyze clusters that contained 
at least 1% of the network’s total users.

Our inductive computational process was iterative; we 
looked for key trends and used extant theory to guide our 
interpretation, a process similar to more traditional qualitative 
coding. In addition to investigating the network structure, we 
also studied the degree of professional connectiveness/insu-
larity among Beltway journalists by examining the types of 
interactions that connected users within a community and 
which newsrooms these interactions came from. We took the 
output of the community detection analysis and used these 
network graphs, along with a frequency analysis of top 
hashtags and top mentions in each community, as well as a 
word cloud analysis of most frequently occurring words 
within the corpus of journalists’ Twitter bios to help us posit 
why certain patterns of interactions might be observed. We 
also looked at prominent accounts in each community and 

Figure 1. Twitter network graph between 2,015 DC journalists.
Note. Nine major clusters are highlighted (colors can be referred in Table 1); node size depends on in-degree centrality.



8 Social Media + Society

referenced our original list of journalists, which contained 
additional information about journalists’ beat specializations, 
past work history, educational background, and time spent in 
Washington. While we did not specifically examine the 
semantic and sentiment content of tweets, frequent hashtags 
and mentions allowed us to compare whether these communi-
ties exhibit strong single-mindedness, giving us insight into 
how knowledge is exchanged and among whom. This inter-
pretative process added an additional, explanatory layer to the 
social network analysis.

Results

Our research questions are intentionally broad—we do not 
expect to be able to definitively describe, in detail, specific 
instances of how journalists are sharing knowledge and 
establishing consensus on or off Twitter, though asking why 
their communities form the way they do on Twitter gives us 
a sense of patterns of interaction at scale. We find that 
Beltway journalism, long presumed to be insular and con-
ventionally understood as a monolithic journalistic culture, 
instead consists of nine major CoPs, each with its own epis-
temic culture. Findings suggest that journalists do seem to be 
in communities with those working at the same news outlets, 
but organizational affiliation alone does not explain the het-
erogeneity. Rather, based on our analysis, these epistemic 
communities can be explained by different rationales, such 
as shared media format, a reputational association, or com-
mon orientations in news coverage.

RQ1. What are the peer-to-peer dynamics in political 
journalism?

Community detection revealed nine major clusters. The 
modularity value was .36, indicating strong community 
structure (Newman & Girvan, 2004). Figure 1 provides a 
visualized network of Twitter interaction among Beltway 
journalists with nodes and edges colored according to the 
group that the nodes belong to.

Each community reflected several distinct dominant news 
outlets (Table 1). A chi-square test for independence reflected 
a very strong relationship between newsrooms and cluster 
assignment (χ2 (11,603) = 37,500, p < .001, Cramer’s V = .67), 
confirming that Beltway journalists indeed clustered accord-
ing to their professional affiliations, though this alone did not 
tell us much about underlying logics of the clusters 
themselves.

RQ2. Why might these community dynamics occur?

RQ3. What kind of knowledge is shared by/among politi-
cal journalists?

Using inductive computational analysis, we relied on bio-
graphical data, word cloud insights, and hashtag/mention 

analysis to interpret these nine communities. An assessment 
of in-group interactions provided us with a measure of “insu-
larity” for each cluster. We identified those nine communities 
as elite/legacy; congressional journalism; CNN; television 
(producers); local political news; regulatory journalism; for-
eign affairs; longform/enterprise; and social issues. In the 
following section, we further describe our rationale for 
assigning these characterizations to each community (RQ2). 
We use top hashtags, mentions, and the community charac-
terization from RQ2 as indicators of the types of sense-mak-
ing processes at work within these clusters (RQ3). As the 
analysis was inductive, analysis of RQ2 and RQ3 worked 
recursively, with insight from one query informing the other, 
and thus are discussed together.

The Elite/Legacy Community

Based on our analysis, Cluster 19 was the largest community. 
It can be thought of as the elite/legacy community: it con-
tained the largest grouping of legacy news outlets, suggest-
ing a dense clustering of the most esteemed news brands 
among each other. Outlets included The Washington Post, 
NPR, The New York Times, and NBC News, and a smaller but 
still notable portion of Politico journalists. Word clouds 
helped reveal trends in the Twitter bios of these journalists, 
with “politics” and “White House” being the dominant self-
descriptions of coverage areas, suggesting that these journal-
ists are more likely to be covering general interest political 
news and may spend most of their time at The White House. 
RQ3 queries what kind of knowledge is being discussed. 
Proxies such as top hashtags and mentions suggest this clus-
ter is focused on general interest political news. Top hashtags 
include a Pennsylvania House of Representatives special 
election, the March for Our Lives, the Olympics, and Syria.4 
This is further bolstered by the fact that the PressSec handle 
is among the top five mentions, suggesting that these jour-
nalists are on hand to cover the press secretary or are other-
wise concerned with reporting information from The White 
House. Notably, this is the largest cluster (30.2% of our sam-
ple) and also highly insular—of the tweets from journalists 
in this group, 68.1% are to other journalists in this cluster, 
providing further support for RQ3 and our concern about 
insular epistemic communities.

The Congressional Journalism Community

Cluster 0, the second largest community of journalists, 
included journalists from Bloomberg, Politico, the AP, The 
Wall Street Journal, CQ/Roll Call, and C-SPAN. Findings 
suggest this epistemic community was organized around 
peer-to-peer relationships of journalists who were “inside 
Beltway journalists” with topical beats and whose mandate it 
is to cover what it is happening in Congress (RQ2). Further 
support for this analysis emerged from the top five hashtags. 
The top hashtags were “wonky”—pharma, biotech, FDA, 



Usher and Ng 9

opioid crisis, and CDC, giving us a sense that the knowledge 
being exchanged was subject-specific (insight into RQ3). 
While the hashtags might suggest a health policy focus, the 
word cloud and bio data revealed a wider range of reporting 
responsibilities, such as tech, banks, trade, health, and busi-
ness (RQ2 informed by RQ3). “Policy” jumped as a weighted 
word; the weighting of “Politico Pro” reflected the presence 
of Politico journalists who work for a separate, subscription-
only service focused on niche issues; these journalists are 
paid to be beat experts covering Congress. But it was not so 
niche that it was detached from broader conversations, and 
top mentions are primarily of other media organizations and 
the President’s Twitter account. This builds support for jour-
nalists building knowledge (or at least discussing it) from the 
work of other journalists, with over 56% of the tweets in this 
cluster directed at the in-group (RQ3), and for specific atten-
tion paid to Congressional developments (the AP and CSPAN, 
both of which provide gavel-to-gavel coverage; RQ2).

The CNN Cluster

Cluster 8 can be defined as the CNN cluster. While the clus-
ter was not entirely homogeneous, CNN journalists were 
over 50% of the cluster’s composition (RQ2) Notably, Jake 
Tapper, the most influential journalist in our network as mea-
sured by weighted in-degree, promotes and is promoted by 
the CNN community. The following top three mentions sug-
gested a preoccupation with organizational branding: @
CNNPolitics, @TheLeadCNN (the show hosted by Jake 
Tapper), and @CNN itself. Top hashtags included references 
to Tapper’s weekend show, CNN State of the Union, a spe-
cial election congressional race in Pennsylvania, and the 
CPAC conference that happened outside Washington during 
data selection. The PressSec account also appeared as a top 
mention, perhaps indicative of CNN’s highly public “battle” 
with the Trump White House. Overall, in assessing RQ3, this 
CNN cluster suggests a dense peer-to-peer network where 
CNN content is amplified and reamplified, as well as a focus 
on “inside the Beltway” interests such as CPAC and, possi-
bly, CNN’s relationship with The White House, a “CNN 
Twitter,” that was highly self-referential and insular (57.99% 
of the tweets were within and among the cluster).

The Television (Producer) Cluster

In Community 2, the three biggest news organizations repre-
sented were ABC News, Fox News, and CBS News. 
Interestingly, two other TV networks were in different clus-
ters: CNN (on its own) and NBC (in a mix of primarily leg-
acy, newspaper outlets). This is likely because NBC has 
multiple platform divisions, namely, broadcast, cable 
(MSNBC), and a large digital team responsible for text-based 
reporting; its correspondents may have more common 
ground within the elite/legacy cluster with the other TV net-
works. While one might presume Fox News journalists 

would not be engaged with news organizations that the net-
work accuses of left-wing bias, this was not the case. In try-
ing to unpack the inclusion of Fox journalists in the television 
community, we considered additional factors, such as 
whether or not there were strong ties like past shared work 
history. The most notable explanation for peer-to-peer rela-
tionships within this community was that these journalists 
mostly self-described as TV news producers (RQ2). Hashtags 
reflected interests in topics beyond just political news, such 
as the Super Bowl and the Olympics, suggesting television 
specific-news judgment with an eye toward entertainment 
(Lotz, 2009). Notably, this was the only cluster to have 
#breaking as a top hashtag. This may reflect the importance 
of the producers’ role in flagging emerging news stories and 
considering their merit for possible segments on their news 
shows. Inquiry into the CoP of producers, wherein Twitter 
facilitates surveilling other producers’ possible booking and 
segment-planning decisions, could provide additional evi-
dence of mimicry and consensus formation (RQ3).

Community of Longform/Enterprise

Cluster 5 is a longform/enterprise cluster. Members’ Twitter 
bios contained a nuanced mix of specialty political beats. 
The word “investigative” was featured prominently, as were 
other words, such as “justice,” “immigration,” “security,” 
and “national security,” “supreme”(court), and, amusingly, 
“nerd.” Top hashtags, while reflecting dominant issues in the 
news, also suggested more thematic rather than episodic cov-
erage; this was the only cluster that had #metoo and #scotus 
as top hashtags. Similarly, “pew trusts” appeared as a top 
mention, which was the only top-ranking reference to a 
thinktank across our data set, suggesting that these journal-
ists may be sharing knowledge about these thematic stories 
relevant beyond the day’s news (RQ3). The outlets that were 
most represented in this cluster were Buzzfeed, McClatchy, 
and The Atlantic, all of which self-described as avoiding “the 
stories of the day”-type of reporting and instead focus on 
impact-driven scoops or insight analyses (Critchlow, 2015; 
McClatchy DC correspondent, personal communication, 
March 2, 2018; RQ2).

The “Local” Political News Community

Cluster 10 is a Washington local news cluster. Washington 
local news, which serves the largest concentration of fed-
eral employees in the United States, also anecdotally may 
provide more political news adapted for a local level. Not 
surprising for locals who were experiencing ongoing frus-
tration over DC’s subway, the @wmata metro account was 
a top mention. One of the top hashtags was #marchforour-
lives, which reflects local interest in political news. As 
with most other clusters, the top mentions outside the net-
work of Beltway journalists’ accounts were self-referential 
to the most-represented news outlets. This community of 



10 Social Media + Society

Washington journalists within the larger Washington polit-
ical journalism Beltway was the most insular, as 80.48% of 
these tweets were in-group.

Communities of Regulatory Journalists, Foreign 
Affairs, and Social Issues

Clusters 4, 7, and 1 also showed coherence in their topical 
connectivity. Cluster 4 was dominated by Bloomberg BNA 
(46.09% of the cluster) and also included specialty news out-
lets such as S&P Global Market Intelligence and E&E News. 
The top hashtags reflected regulatory concerns such as #osha 
(occupational health and safety), #epa (environmental pro-
tection agency), and #omnibus (a reference to an infrastruc-
ture bill). Cluster 7 journalists were predominantly focused 
on issues in foreign affairs and the US military. Members’ 
Twitter bios included “pentagon,” “foreign,” and “military.” 
Top hashtags all reflected a preoccupation with foreign 
affairs (#isis, #china, etc.). Finally, Cluster 1, the smallest 
cluster, included outlets concerned with social issues, such as 
education and gun violence. Each of these three clusters 
showed smaller, topically specific rationales for peer-to-peer 
engagement; biographical data and outlets offered a clue to 
their composition and community rationale, while key men-
tions and hashtags served as proxies for knowledge 
exchanged (RQ2 and RQ3),

Overall, this analysis of CoPs gives us an understanding 
of some of the organizing logics of the various Beltway jour-
nalism Twitter communities. We cannot answer what each 
journalist happens to be learning from Twitter and how her 
engagement on Twitter informs her work. However, we can 
see peer-to-peer engagement at scale. Within an already 
insular system of knowledge production and sense-making, 
we find concentrated clusters that are more variegated than a 
single version of “Beltway journalism.” Nonetheless, these 
CoPs show smaller silos, or microbubbles, of high-ego actors 
who have tremendous power to shape public information but 
who are also vulnerable to groupthink, blind spots, and the 
warped logic that results when an epistemic community folds 
in on itself, as Knorr Cetina warns.

Discussion

This project offers two interventions to augment our under-
standing about the news production processes of elite politi-
cal journalists. First, it introduces the productive potential of 
a CoP approach, which can illuminate not just how peer-to-
peer dynamics influence social learning, consensus, and 
shared practices, but also provides an entry-point for critical 
inquiry into the consequences of powerful actors inhabiting 
insular epistemic communities. Second, the article suggests a 
way to use big (or biggish) data from social media platforms 
in ways that can be conducive to more qualitative, humanis-
tic questions of the kind we have asked here. Indeed, research 

questions approached from this perspective do not have to 
have definitive answers resolved by the case.

Our approach shows how loosely distributed networks of 
powerful political journalists self-organize in different CoPs 
(RQ1) and then explores the different logics for these CoPs 
(RQ2) to consider what kinds of knowledge-generation and 
shared practices might emerge (RQ3). Our findings suggest 
even smaller, more insular communities of journalism that 
function as silos or even “microbubbles” with their own sets 
of concerns. We know from existing research that these jour-
nalists are engaging in story ideas, joking around, and bur-
nishing their own careers (Kreiss, 2016; Mourão, 2015). 
They are doing so, however, within even smaller communi-
ties of like-minded journalists that have been previously con-
sidered. If journalists are talking to even smaller groups of 
journalists who share similar orientations, there is a real con-
cern about the limitations of these epistemic communities in 
generating knowledge and information for the public. In 
these insular epistemic communities, newness is controlled 
and incorporated within these power domains (Barnes, 
2005), and critique that veers outside the norm of general 
banter or the emerging consensus may be disregarded. 
Indeed, these microbubbles risk folding in on themselves, as 
Knorr Cetina (1999) suggests. In particular, it is concerning 
that CNN journalists are tweeting mostly to other CNN jour-
nalists about CNN. Even if this is an organizational mandate, 
it nonetheless serves as a powerful echo chamber that leaves 
CNN’s internal sense about what news matters unchecked 
and reconfirmed by those who work there. On Twitter, a plat-
form absolutely integral to the political journalism news pro-
duction process, CNN journalists have limited engagement 
with other Beltway journalists.

Previous research has suggested that journalists care more 
about their own branding than their organization’s; this self-
branding tactic is a hedge against the precarity of the news 
industry (Molyneux, 2015; Usher, 2014). However, across 
all clusters, we find that top mentions are often referential to 
the top media organizations represented in each cluster, 
which suggests Beltway journalists prioritize branding the 
organization they work for. Organizational affiliation is not a 
sufficient enough explanation for the heterogeneity of the 
communities, but these organizational ties provide an impor-
tant counterpoint for previous presumptions about self-
branding practices among journalists.

Would these communities look different given a different 
temporal slicing of the data? Perhaps. While the specific con-
centrations of the makeup of journalists might change, the 
underlying rationale for each epistemic community’s prac-
tice orientation around specific knowledge production would 
likely be consistent, given what we have observed based on 
the biographical details of Twitter bios, the range of organi-
zations represented, and thematic consistencies among 
hashtags and mentions. Here, we focused on a single net-
work in isolation, but the triangulation of several network 



Usher and Ng 11

structures (e.g., of follower networks) might illuminate other 
insights. We acknowledge our normativity in suggesting that 
media diversity in Washington should be desirable. However, 
these patterns on Twitter may be suggestive of an even more 
self-reinforcing journalistic experience than research has 
previously acknowledged.

Normativity aside, this research reveals that Washington 
journalism is far more nuanced than it might seem. In addi-
tion to the sub-communities of journalists, the epistemic 
foundations for their clusters suggest the importance of 
remembering there are multiple audiences and multiple 
stakeholders outside the generally accepted waterfall sche-
matic of press–politics–audiences (Entman, 2004). These 
sub-clusters within Washington may be less immediately vis-
ible but they are not necessarily less important, and their 
potential influence on political actors and other journalists, 
not to the public, deserves our attention.

This research calls for more detailed analyses of media 
elitism in the United States and elsewhere. The dangers of 
journalists having limited perspectives are real. While this 
study does not purport to show possible worsening over 
time, it does provide support that shows siloed communities 
of journalists and thus offers an important, empirically 
grounded caveat about their vulnerability to groupthink and 
blind spots. While political journalists have been tradition-
ally explored as part of the source-journalist “tango” (Gans, 
1979) and examined within a broader political communica-
tion structure (cf., Entman, 2004), to stretch a metaphor, we 
argue it is important to consider what happens when journal-
ists are dancing with other journalists, who they pick as part-
ners, and the songs they dance to.

Acknowledgements

The authors would like to thank Matthew S. Weber, Peter Van 
Aelst, Laura Wrubel, Suzy Khimm, and Daniel Wagner for their 
feedback and assistance.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect 
to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, author-
ship, and/or publication of this article.

ORCID iD

Nikki Usher  https://orcid.org/0000-0001-7297-4427

Notes

1. We sidestep the problematizing of “knowledge” and “com-
munity” as concepts in this article, as Knorr Cetina and oth-
ers have made this central to their point of inquiry in the area 
literature.

2. Data from https://www.journalism.org/2015/12/03/the- 
numbers-overall/

3. Github link: https://github.com/margaretnym/BeltwayJournalists
4. The list of top hashtags also surfaces AMR, which stands for 

Andrea Mitchell Reports; Mitchell tags all of her tweets with 
#AMR, which significantly inflated this hashtag count.

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Author Biographies

Nikki Usher (PhD, USC Annenberg School of Communication) is 
an associate professor in the Department of Journalism and faculty 
affiliate in Communication and Political Science at The University 
of Urbana-Champaign. She is the author of two books, Making 
News at the New York Times (2014) and Interactive Journalism: 
Hackers, Data, and Code (2016).

Yee Man Margaret Ng (PhD, University of Texas) is an assistant 
professor in the Department of Journalism and Department of 
Computer Science (faculty affiliate) at The University of Illinois 
Urbana–Champaign. Her research interests include computational 
social science, journalism, and communication technology.

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