In an effort to better understand the theoretical landscape of my chosen academic field, I have created a co-citation network visualization based on bibliographies found in nine major communication journals. The nine journals chosen are some of the best-known and longest-running in the field:
- Communication Research
- Communication Theory
- Critical Studies in Media Communication
- Human Communication Research
- Journal of Broadcasting & Electronic Media
- Journal of Communication
- Journal of Computer-Mediated Communication
- Journalism & Mass Communication Quarterly
- Political Communication
Co-citation is a well-established technique for mapping academic disciplines (among other applications). The basic idea is that two publications are considered linked or “co-cited” when they appear in the same article’s reference list. After a basic co-citation network is created, a community-detection algorithm can be run to generate an organic impression of a discipline’s major subtopics and authors. In this map, the co-citation communities identified by the algorithm are grouped together by color. I doubt the specific groupings will surprise any seasoned scholars, but they will certainly help beginners (like me) get a sense of what our colleagues in other divisions have been thinking about over the past decade.
Maps similar to this one have been created for sociology and philosophy, and I credit those authors for giving me the idea to create this one. In doing so I relied heavily on Neal Caren’s excellent Python script for scraping citation data from Web of Knowledge (WoK). In the next section I give a guided tour of the map, after which I provide additional methodological details.
One of the first things you’ll notice about the map is that publications are listed by first author only. This is how WoK stores references, but in most cases it shouldn’t be too hard to figure out which article or book is intended. Also, a few very popular articles probably have at least one duplicate node–I did not attempt to clean this dataset because I couldn’t figure out a non-manual way to do so.
Only highly-cited items appear on this map, a decision made for the sake of both parsimony and technical limitations. In order to make the initial cut, a publication had to 1) have at least ten citations according to WoK and 2) be co-cited on at least five reference lists with another publication meeting the first criterion. In this way, a network of 80,880 unique cited publications* and 3,878,211 co-citation links drawn from 2,834 seed articles was whittled down to 1,124 pubs and 6,092 links.
If you mouse over a given publication you’ll see the others to which it is connected. A link between two publications means that the two are co-cited at least five times. Thicker links mean more co-citations. Intra-community links share the community’s color; inter-community links take on one of the two community’s colors at random. A publication’s node size reflects the number of bibliographies in which it appears.
The nine colored communities in this network represent the nine most densely-interlinked subtopics addressed in the journals. The community detection algorithm identified a total of 28 link clusters, so nine is an arbitrary number (I had to stop somewhere). These top nine represent about a third of the communities found, but this third contains 89.5% (1,006/1,124) of all the pubs that met the initial inclusion criteria.
Here I give each community a label and a short description, but I can’t claim expertise on all of them, so corrections and suggestions are welcome.
- __ Interpersonal communication, offline and on. Unsurprisingly, this community was well-represented in JCMC. It incorporates pieces from both the digital age and long before, with Walther, Berger, and Knobloch being especially prominent. Classic works by Goffman, Spears, Altman & Taylor, and Parks & Floyd can also be seen.
- __ Race and media. One of the smaller communities, this one builds on foundational work in both media studies and effects (e.g. Entman, Dixon, Gilliam, Valentino) and psychology (Fiske, Devine). Much of it focuses on pejorative perceptions of African Americans by whites.
- __ Parasocial interaction/uses & gratifications. Drawing heavily on psychologists such as Bandura and Fishbein, this cluster examines how and why people consume media (especially popular media) as well as their relationships with the characters on the screen. (This is one of the ones I know less well, so let me know if there’s a better way to describe it.)
- __ Selective exposure/political polarization. From the foundational work of Festinger and Sears & Freedman in the 1950s and 60s to Sunstein’s Republic.com, this community focuses on how people select, reject, and justify media content and the consequences for their opinions, beliefs, and emotions.
- __ Visual images and cognition/knowledge gap. This cluster is heavily anchored in the work of Lang, Grabe, Reeves, and Newhagen. Its objects of study are the influence of visual media on cognition, specifically memory, emotion, and knowledge. The knowledge gap concept is also prominent here. (Again, I’m not an expert here, so please correct as appropriate!)
- __ Civic engagement/political participation/deliberation/social capital. This cluster is concerned with the roles of media and communication in citizens’ engagement with politics and their communities. The second largest community by internal links, it incorporates leading research from sociology (Coleman, Wellman, Granovetter) and political science (Putnam, Norris, Huckfeldt) in addition to communication.
- __ Social cognition/cultivation theory/statistical methods. This cluster shares a few links with the “visual images” and “parasocial interaction” cluster but is distinct from both. With Petty & Cacioppo’s classic book on the elaboration likelihood model as its primary anchor, this research investigates concepts such as information processing, emotion, persuasion, influence, and attitudes as they pertain to communication. Interestingly, major pieces on statistical analysis by Holbert & Stephenson, Bollen, and Baron & Kenny are also included here.
- __ Third-person effect/hostile media effect. This community is home to the closely-related hostile media and third-person effects, both of which involve people’s beliefs about how media messages relate to others. Though its originator (Davison) was a scholar of journalism and sociology, later third-person effect research increasingly relies on concepts borrowed from psychology (e.g. Eveland, Nathanson, Detenber, & Mcleod, 1999; Henriksen & Flora, 1999; Hoffner et al., 1999).
- __ Agenda-setting/framing/priming. In a development that will surprise no one, the largest cluster by far is devoted to the study of three interrelated media effects: framing, priming, and agenda-setting. The major works and authors here will be known to nearly all students of mass communication: Iyengar, Entman, McCombs, Zaller, Gamson, Shoemaker, Bennett, Price, Scheufele, and many more…
There is much to say about these clusters–much more than I have time to articulate–so I’ll limit myself to an observation and a related caveat. First, critical theory is conspicuous in its absence from these clusters. Marx, Foucault, Adorno, Williams, Baudrillard, Butler, and other critical stalwarts are nowhere to be found among this list of landmark works. Among those critical theorists who do make the cut are Chomsky, Habermas, Hall, and Bourdieu, though I leave to the reader the exercise of finding them on the map.
One reason for the omission may be the use of the journal as the sampling unit. Much critical work is published in books, and while many books appear on the map, it is clear that journal articles largely tend to cite other journal articles. And in communication, the better-known journals tend to publish work that is quantitative, empirical, epistemologically social-scientific, and American in focus. So the major caveat for this map is that it almost certainly underrepresents work that is qualitative, purely theoretical, critical, and non-American. Unfortunately, there is no easy way to integrate books into it, and even if there were, there is no preexisting list of the most-cited books in communication.
Additional method notes
From each journal, all reference lists from all research articles (specifically excluding book reviews and similar) available in WoK between 2013 and 2003 were extracted on September 3, 2013. A few items from 2002 were included for some journals.
For those who are interested, here is a quick summary of how I created this map:
- Downloaded full reference lists from WoK for all articles (excluding book reviews etc.) published between 2003-Sept 2013 from the above journals in plain-text format
- Used Neal Caren’s Python script to create a network edgelist based on the criteria above
- Opened edgelist in Gephi and ran the “fast unfolding” community detection algorithm (Blondel, 2008) to identify network clusters
- Rearranged graph layout to color and group together network communities
- Exported final graph file in GEXF format
- Created web visualization with GEXF.js
The raw data for the map (1,124 nodes/6,092 edges) can be downloaded here.
If you have any questions about how I made the map, I’d be happy to answer them. Also, if you have suggestions for additional journals to add, let me know and I may be able to do it–but GEXF.js is limited in the amount of network data it can display so there’s no guarantee.
*The true number is somewhat less than this, as some pubs are listed under different names due to incompatible citation practices and miscellaneous citation errors.