More and more scholarly attention is paid to dissecting discipline of communication research under the microscope thereby aiming at revealing foci of scientific interest. The lion’s share of research has hereby focused either on the supply side of research examining what topics scholars write about or at the popularity side of research shedding light on what scientific publications receive the most citations. Building up on this, we argue that these research strands are inadequate to the task of exhaustively identifying foci of scientific interest. Tailoring for the fragmented topical landscape of communication research, we propose an integrative combination of three metrics: supply, popularity, and prestige of research topics. By means of topic modeling, citation counts and citation networks, our study showcases how our approach is able to reveal the intellectual architecture of our discipline in order to identify relevant paths for further scientific inquiry.
AngP. H.Knobloch-WesterwickS.AguadedI.Muñoz-UribeJ. F.WassermanH.AthiqueA. (2019). Intellectual balkanization or globalization: The future of communication research publishing. Journalism & Mass Communication Quarterly, 96(4), 963–979. https://doi.org/10.1177/1077699019878461
3.
AntonsD.KleerR.SalgeT. O. (2016). Mapping the topic landscape of JPIM, 1984-2013: In search of hidden structures and development trajectories. Journal of Product Innovation Management, 33(6), 726–749. https://doi.org/10.1111/jpim.12300
4.
BergerC. R. (1991). Chautauqua: Why are there so few communication theories? Communication theories and other curios. Communication Monographs, 58, 101–113. https://doi.org/10.1080/03637759109376216
5.
BleiD. M.LaffertyJ. D. (2007). A correlated topic model of science. The Annals of Applied Statistics, 1(1), 17–35. https://doi.org/10.1214/07-AOAS114
BorahP. (2017). Emerging communication technology research: Theoretical and methodological variables in the last 16 years and future directions. New Media & Society, 19(4), 616–636. https://doi.org/10.1177/1461444815621512
9.
BornmannL.DanielH. D. (2008). What do citation counts measure? A review of studies on citing behavior. Journal of Documentation, 64(1), 45–80. https://doi.org/10.1108/00220410810844150
10.
BornmannL.MutzR.NeuhausC.DanielH. D. (2008). Citation counts for research evaluation: Standards of good practice for analyzing bibliometric data and presenting and interpreting results. Ethics in Science and Environmental Politics, 8(1), 93–102. https://doi.org/10.3354/esep00084
11.
BrownG.YuleG. (1983). Discourse analysis. Cambridge University Press.
12.
BrunsA. (2019). After the ‘APIcalypse’: Social media platforms and their fight against critical scholarly research. Information, Communication & Society, 22(11), 1544–1566. https://doi.org/10.1080/1369118X.2019.1637447
13.
BürknerP. C. (2017). brms: An R package for Bayesian multilevel models using Stan. Journal of Statistical Software, 80(1), 1–28. https://doi.org/10.18637/jss.v080.i01
CarpenterC. J. (2019). Cognitive dissonance, ego-involvement, and motivated reasoning. Annals of the International Communication Association, 43, 1–23. https://doi.org/10.1080/23808985.2018.1564881
ChungC. J.BarnettG. A.KimK.LackaffD. (2013). An analysis on communication theory and discipline. Scientometrics, 95(3), 985–1002. https://doi.org/10.1007/s11192-012-0869-4
18.
ClausetA.ShaliziC. R.NewmanM. E. (2009). Power-law distributions in empirical data. SIAM Review, 51(4), 661–703. https://doi.org/10.1137/070710111
19.
CooperR.PotterW. J.DupagneM. (1993). A status report on methods used in mass communication research. The Journalism Educator, 48(4), 54–61. https://doi.org/10.1177/107769589304800408
20.
D’UrsoS. C. (2009). The past, present, and future of human communication and technology research: An introduction. Journal of Computer-Mediated Communication, 14(3), 708–713. https://doi.org/10.1111/j.1083-6101.2009.01459.x
FranceschetM. (2010). The difference between popularity and prestige in the sciences and in the social sciences: A bibliometric analysis. Journal of Informetrics, 4(1), 55–63. https://doi.org/10.1016/j.joi.2009.08.001
23.
FreelonD. (2020). On writing in communication and media studies: Two brief points on publication impact. International Journal of Communication, 14, 427–429. https://ijoc.org/index.php/ijoc/article/view/13829
24.
GriffinD. J.BolkanS.HolmgrenJ. L.TutzauerF. (2016). Central journals and authors in communication using a publication network. Scientometrics, 106(1), 91–104. https://doi.org/10.1007/s11192-015-1774-4
25.
GriffithsT. L.SteyversM. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101, 5228–5235. https://doi.org/10.1073/pnas.0307752101
GüntherE.DomahidiE. (2017). What communication scholars write about: An analysis of 80 years of research in high-impact journals. International Journal of Communication, 11, 3051–3071. https://ijoc.org/index.php/ijoc/article/view/6989
28.
HaJ. H.BoyntonL. (2014). Has crisis communication been studied using an interdisciplinary approach? A 20-year content analysis of communication journals. International Journal of Strategic Communication, 8(1), 29–44. https://doi.org/10.1080/1553118x.2013.850694
IoannidisJ. P.BaasJ.KlavansR.BoyackK. W. (2019). A standardized citation metrics author database annotated for scientific field. PLoS Biology, 17(8), Article 3000384. https://doi.org/10.1371/journal.pbio.3000384
31.
JacobiC.Van AtteveldtW.WelbersK. (2016). Quantitative analysis of large amounts of journalistic texts using topic modelling. Digital Journalism, 4(1), 89–106. https://doi.org/10.1080/21670811.2015.1093271
32.
JohnsonB. T.Scott-SheldonL. A. J.SnyderL. B.NoarS. M.Huedo-MedinaT. B. (2008). Contemporary approaches to meta-analysis in communication research. In HayesA. F.SlaterM. D.SnyderL. B. (Eds.), The sage sourcebook of advanced data analysis methods for communication research (pp. 311–347). SAGE.
33.
KamhawiR.WeaverD. (2003). Mass communication research trends from 1980 to 1999. Journalism & Mass Communication Quarterly, 80(1), 7–27. https://doi.org/10.1177/107769900308000102
34.
KimS. T.WeaverD. (2002). Communication research about the Internet: A thematic meta-analysis. New Media & Society, 4(4), 518–538. https://doi.org/10.1177/146144402321466796
35.
KimY. J.HollingsheadA. B. (2015). Online social influence: Past, present, and future. Annals of the International Communication Association, 39(1), 163–192. https://doi.org/10.1080/23808985.2015.11679175
36.
LeeH.KangP. (2018). Identifying core topics in technology and innovation management studies: A topic model approach. The Journal of Technology Transfer, 43(5), 1291–1317. https://doi.org/10.1007/s10961-017-9561-4
37.
LeeK.JungH.SongM. (2016). Subject-method topic network analysis in communication studies. Scientometrics, 109(3), 1761–1787. https://doi.org/10.1007/s11192-016-2135-7
38.
LevineT. R. (2010). Rankings and trends in citation patterns of communication journals. Communication Education, 59(1), 41–51. https://doi.org/10.1080/03634520903296825
39.
LinY.KaidL. L. (2000). Fragmentation of the intellectual structure of political communication study: Some empirical evidence. Scientometrics, 47(1), 143–164. https://doi.org/10.1108/14691931211276124
40.
MaierD.WaldherrA.MiltnerP.WiedemannG.NieklerA.KeinertA.PfetschB.HeyerG.ReberU.HäusslerT.Schmid-PetriH.SilkeA. (2018). Applying LDA topic modeling in communication research: Toward a valid and reliable methodology. Communication Methods and Measures, 12(2–3), 93–118. https://doi.org/10.1080/19312458.2018.1430754
41.
ManeK. K.BörnerK. (2004). Mapping topics and topic bursts in PNAS. Proceedings of the National Academy of Sciences, 101(Suppl. 1), 5287–5290. https://doi.org/10.1073/pnas.0307626100
42.
McElreathR. (2015). Statistical rethinking: A Bayesian course with examples in R and Stan. Chapman and Hall/CRC.
43.
MertonR. K. (1938). Science, technology and society in seventeenth-century England. Osiris, 4, 360–632. https://doi.org/10.1086/368484
44.
NeuendorfK. A. (2016). The content analysis guidebook. SAGE.
45.
NeumannW. R.GuggenheimL. (2011). The evolution of media effects theory: A six-stage model of cumulative research. Communication Theory, 21(2), 169–196. https://doi.org/10.1111/j.1468-2885.2011.01381.x
46.
OppenheimC. (1995). The correlation between citation counts and the 1992 research assessment exercise ratings for British library and information science university departments. Journal of Documentation, 51(1), 18–27. https://doi.org/10.1108/eb026940
O’SullivanP. B.CarrC. T. (2018). Masspersonal communication: A model bridging the mass-interpersonal divide. New Media & Society, 20(3), 1161–1180. https://doi.org/10.1177/1461444816686104
49.
ParkH.LeydesdorffL. (2009). Knowledge linkage structures in communication studies using citation analysis among communication journals. Scientometrics, 81(1), 157–175. https://doi.org/10.1007/s11192-009-2119-y
50.
ParksM. R. (2014). Big data in communication research: Its contents and discontents. Journal of Communication, 64(2), 355–360. https://doi.org/10.1111/jcom.12090
51.
PaulB.SalwenM. B.DupagneM. (2000). The third-person effect: A meta-analysis of the perceptual hypothesis. Mass Communication & Society, 3(1), 57–85. https://doi.org/10.1207/s15327825mcs0301_04
52.
PengT. Q.WangZ. Z. (2013). Network closure, brokerage, and structural influence of journals: A longitudinal study of journal citation network in Internet research (2000-2010). Scientometrics, 97(3), 675–693. https://doi.org/10.1007/s11192-013-1012-x
PinskiG.NarinF. (1976). Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics. Information Processing & Management, 12(5), 297–312. https://doi.org/10.1016/0306-4573(76)90048-0
55.
PuschmannC. (2019). An end to the wild west of social media research: A response to Axel Bruns. Information, Communication & Society, 22(11), 1582–1589. https://doi.org/10.1080/1369118x.2019.1646300
56.
RauchfleischA. (2017). The public sphere as an essentially contested concept: A co-citation analysis of the last 20 years of public sphere research. Communication and the Public, 2(1), 3–18. https://doi.org/10.1177/2057047317691054
57.
RauchfleischA.SchäferM. S. (2018). Structure and development of science communication research: Co-citation analysis of a developing field. Journal of Science Communication, 17(3), Article A07. https://doi.org/10.22323/2.17030207
RobertsM. E.StewartB. M.TingleyD.LucasC.Leder-LuisJ.GadarianS. K.AlbertsonB.RandD. G. (2014). Structural topic models for open-ended survey responses. American Journal of Political Science, 58(4), 1064–1082. https://doi.org/10.1111/ajps.12103
60.
SoC. (1998). Citation ranking versus expert judgment in evaluating communication scholars: Effects of research specialty size and individual prominence. Scientometrics, 41(3), 325–333. https://doi.org/10.1007/bf02459049
61.
SongH.EberleJ.-M.EiseleO. (2020). Less fragmented than we thought? Toward clarification of a subdisciplinary linkage in communication science, 2010-2019. Journal of Communication, 70(3), 310–314. https://doi.org/10.1093/joc/jqaa009
62.
TomaselloT. K. (2001). The status of Internet-based research in five leading communication journals, 1994-1999. Journalism & Mass Communication Quarterly, 78(4), 659–674. https://doi.org/10.1177/107769900107800403
63.
TomaselloT. K.LeeY.BaerA. P. (2010). “New media” research publication trends and outlets in communication, 1990-2006. New Media & Society, 12(4), 531–548. https://doi.org/10.1177/1461444809342762
64.
WaisbordS. (2019). Communication: A post-discipline. Polity.
XhignesseL. V.OsgoodC. E. (1967). Bibliographical citation characteristics of the psychological journal network in 1950 and in 1960. American Psychologist, 22(9), 778–791. https://doi.org/10.1037/h0024961
67.
YeL.KiE. J. (2012). The status of online public relations research: An analysis of published articles in 1992-2009. Journal of Public Relations Research, 24(5), 409–434. https://doi.org/10.1080/1062726x.2012.723277
68.
ZhangY.LeungL. (2015). A review of social networking service (SNS) research in communication journals from 2006 to 2011. New Media & Society, 17(7), 1007–1024. http://dx.doi.org/10.1177/1461444813520477
69.
ZhouY. B.LüL.LiM. (2012). Quantifying the influence of scientists and their publications: Distinguishing between prestige and popularity. New Journal of Physics, 14(3), Article 033033. https://doi.org/10.1088/1367-2630/14/3/033033
70.
ZhuY.FuK. W. (2019). The relationship between interdisciplinarity and journal impact factor in the field of communication during 1997–2016. Journal of Communication, 69(3), 273–297. https://doi.org/10.1093/joc/jqz012
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
