Map of scientific research on Communication in Spain: study fronts and rankings of authors, publications and institutions [open access article]

por
Scientific research in communication. Spain universities
Source: Trillo-Domínguez and De-Moya-Anegón 2022. Click to access

Abstract

This work presents a current map of scientific research on Communication in Spain, identifying both the research fronts of the publications with the greatest impact over the last three years (2019–2021) and the authors who led such work and their universities of reference. The original methodology applied herein focuses on an analysis of the cited authors.

After a careful selection process, we work with a corpus of more than 800 articles, using Scopus and the VOSviewer software to generate a co-referencing map and throw light on the structure of the Communication field. On the basis of that analysis, we identify nine thematic clusters, with a particular grouping structure, leading authors, and relationships around fields of study such as communication, democracy and power, audiences and media consumption, the media industry, journalistic practice, fact checking and disinformation, journalistic innovation, and SEO journalism.

The ranking of cited authors, where Ramón Salaverría and Rasmus K. Nielsen hold equal first position and the Chilean Claudia Mellado is the only woman at the head of a strong group, is put into context by analyzing their scientific production and the normalized impact in Communication of their institutions. The comparative analysis reveals the elite Spanish authors in Communication (Xosé López-García, Ignacio Aguaded, Andreu Casero-Ripollés, Lluís Codina, and Ramón Salaverría) and shows how universities in Madrid maintain their importance in terms of production but that those in Catalunya have the lead in terms of impact. The research is completed with a map of keyword co-occurrence that confirms the barrage of studies around the Covid crisis and the parallel and growing number of hoaxes (fakes). The research confirms the relevance of and opportunity to apply scientometric techniques to the Communication field.

Keywords

Scientific maps; Science maps; Communication research; Journalism; Scientometrics; Rankings; Authors; Researchers; Software; Universities; Scientific excellence; Trends; Lines of investigation; Impact; Data visualization; VOSviewer; Scopus; Scientific production; Journals; Research groups; Publications; Institutions; Research fronts.

Introduction

Neither Communication nor the Social Sciences can ignore the advances being made by scientometry (from network analysis and bibliometric maps to advanced visualization techniques) in other fields of knowledge. Such advances based on the application of methodologies, software, and tools provide objectivity and rigor to studies as well as data to analyze and evaluate the output of researchers, levels of scientific cooperation, the impact of state funding of science, or its impact on the educational system (Moral-Muñoz et al., 2020): “Measuring is knowing”. We agree with the cited authors in using this quote from Van-Raan (2004), an eloquent statement attributed to Onnes, to describe the growing importance of observation and measurement as a foundation for the construction of science, in any area of knowledge today, of any science. In citing, for example, Asimov (2010), they remind us that modern science emerged when Nature was dissected by measurement methods, thus showing how both professionals and researchers require a set of theoretical and practical tools to quantify, evaluate, and analyze experimental data.

Perhaps we stand before the Achilles’ heel of the Social Sciences: the weakness of and lack of innovation in the scientific method. Authors such as Salaverría (2015), Steensen (2011), and García-Avilés (2021) warn, for example, of the need to innovate in Journalism in terms of both fields of study and research strategies to go beyond surveys, interviews, or case studies.

The update carried out by Moral-Muñoz, Herrera-Viedma, Santisteban-Espejo, and Cobo (2020) on the tools available to do bibliometric and scientometric analyses, including data acquisition sources, performance analysis, and visualization tools, well illustrates the opportunities open to researchers in this digital world (Negroponte, 2000) that is increasingly being transformed into a tyrannical data-driven society where technological progress marks the advances of science (with the accelerated rollout of artificial intelligence), as well as the most everyday objects as reflected in the Internet of Things.

Just as Data Journalism and fact checking are opening the way to counteract the disinformation and fakes that invade the post-truth era resulting from the ubiquity of the Internet and the explosion of social networks, we believe that relying on scientific methods will help research in Communication by guaranteeing an objective foundation with a strong preference for quantitative analysis. All this must of course be carried out without undermining the subsequent necessary interpretation, critical analysis, and discussion of the data. This is essential in both the journalistic field that we take as an example herein as well as the wider area of Communication and Social Sciences that includes it.

From this perspective, and as a starting point to evaluate the connection between Scientometry and the Communication studies that we propose in this work, we must highlight the growing importance of “bibliometry,” using the term coined by Pritchard (1969) for the study of scientific publications, considering the outstanding development that this discipline is experiencing in parallel with the dizzying progress of science and the development of platforms and databases.

Source: Trillo-Domínguez and De-Moya-Anegón 2022. Click to access

On the one hand, these collect the enormous amount of data indexed in academic journals, books, patents, and proceedings (titles, authors, citations, keywords, institutions, etc.) while providing, on the other, a valuable sample to carry out scientific evaluation research using bibliometric techniques (Gutiérrez-Salcedo et al., 2018) that we consider perfectly extrapolable to the Communication field.

(…)

Downloads

Citation

Trillo-Domínguez, Magdalena; De-Moya-Anegón, Félix (2022). “Map of scientific research on Communication
in Spain: study fronts and rankings of authors, publications and institutions”. Profesional de la información, v.
31, n. 1, e310112. https://doi.org/10.3145/epi.2022.ene.12

Cited references

  • Éric; Campbell, David; Gingras, Yves; Larivière, Vincent (2009). “Comparing bibliometric statistics obtained from the Web of Science and Scopus”. Journal of the American Society for Information Science and Technology, v. 60, n. 7, pp. 1320-1326. https://doi.org/10.1002/asi.21062
  • Asimov, Isaac (2010). A short history of chemistry – An introduction to the ideas and concepts of chemistry. New York: Doubleday & Co. Inc. ISBN: 0313207690
  • Börner, Katy; Chen, Chaomei; Boyack, Kevin W. (2003). “Visualizing knowledge domains”. Annual Review of information science and technology, v. 37, pp. 179-255. https://doi.org/10.1002/aris.1440370106
  • Boyack, Kevin W.; Klavans, Richard; Börner, Katy (2005). “Mapping the backbone of science”. Scientometrics, v. 64, n. 3, pp. 351-374. https://doi.org/10.1007/s11192-005-0255-6
  • Chen, Chaomei (2006). “CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature”. Journal of the American Society for Information Science and Technology, v. 57, n. 3, pp. 359-377. https://doi.org/10.1002/asi.20317
  • Codina, Lluís (2021). What is a scientific article? IMRaD and JARS: Components and meaning. https://www.lluiscodina.com/imrad-jars-scientific-paper
  • Corera-Álvarez, Elena; De-Moya-Anegón, Félix (2009). “Chemistry in Spain: bibliometric analysis through Scopus”. Chemistry today, v. 27, n. 6, pp. 61-64.
  • De-Moya-Anegón, Félix; Vargas-Quesada, Benjamín; Chinchilla-Rodríguez, Zaida; Corera-Álvarez, Elena; Muñoz-Fernández, Francisco J.; Herrero-Solana, Víctor (2007). “Visualizing the marrow of science”. Journal of the American Society for Information Science and Technology, n. 58, v. 14, pp. 2167-2179. https://dl.acm.org/doi/10.5555/1324533.1324535
  • De-Nooy, Wouter; Mrvar, Andrej; Batagelj, Vladimir (2005). Exploratory social network analysis with Pajek. Cambridge: Cambridge University Press.
  • Ding, Xue; Yang, Zhong (2020). “Knowledge mapping of platform research: a visual analysis using VOSviewer and CiteSpace”. Electronic commerce research. https://doi.org/10.1007/s10660-020-09410-7
  • Ellegaard, Ole; Wallin, Johan A. (2015). “The bibliometric analysis of scholarly production: How great is the impact?”. Scientometrics, v. 105, pp. 1809-1831. https://doi.org/10.1007/s11192-015-1645-z
  • Fabregat-Aibar, Laura; Barberà-Mariné, M. Glòria; Terceño, Antonio; Pié, Laia (2019). “A bibliometric and visualization analysis of socially responsible funds”. Sustainability, v. 11, n. 9. https://doi.org/10.3390/su11092526
  • García-Avilés, José-Alberto (2021). “Review article: Journalism innovation research, a diverse and flourishing field (2000-2020)”. Profesional de la información, v. 30, n. 1, e300110. https://doi.org/10.3145/epi.2021.ene.10
  • Guerrero-Bote, Vicente P.; De-Moya-Anegón, Félix (2015). “Analysis of scientific production in food science from 2003 to 2013”. Journal of food science, v. 80, n. 12, pp. R2619-R2626. http://doi.org/10.1111/1750-3841.13108
  • Gutiérrez-Salcedo, María; Martínez, M. Ángeles; Moral-Muñoz, José A.; Herrera-Viedma, Enrique; Cobo, Manuel J. (2018). “Some bibliometric procedures for analyzing and evaluating research fields”. Applied intelligence, v. 48, n. 5, pp. 1275-1287. https://doi.org/10.1007/s10489-017-1105-y
  • Hane, Paula J. (2004). “Elsevier announces Scopus service”. Information today, 15 March. http://newsbreaks.infotoday.com/nbreader.asp?ArticleID=16494
  • Herrero-Solana, Víctor; Trillo-Domínguez, Magdalena (2014). “Twitter Brand Directors: el efecto marca en las redes sociales de los directores de medios españoles”. Estudios sobre el mensaje periodístico, v. 20, n. 1, pp. 131146. https://doi.org/10.5209/rev_ESMP.2014.v20.n1.45223
  • Jacsó, Péter (2011). “The h-index, h-core citation rate and the bibliometric profile of the Scopus database”. Online information review, v. 35, n. 3, pp. 492-501. https://doi.org/10.1108/14684521111151487
  • Klavans, Richard; Boyack, Kevin W. (2006). “Quantitative evaluation of large maps of science”. Scientometrics, v. 68, n. 3, pp. 475-499. https://doi.org/10.1007/s11192-006-0125-x
  • Leydesdorff, Loet (2004). “Clusters and maps of science journals based on bi-connected graphs in Journal Citation Reports”. Journal of documentation, v. 60, n. 4, pp. 371-427. https://doi.org/10.1108/00220410410548144
  • Leydesdorff, Loet; De-Moya-Anegón, Félix; Guerrero-Bote, Vicente P. (2010). “Journal maps on the basis of Scopus data: A comparison with the Journal Citation Reports of the ISI”. Journal of the American Society for Information Science and Technology, v. 61, n. 2, pp. 352-369. https://doi.org/10.1002/asi.21250
  • Leydesdorff, Loet; Rafols, Ismael (2009). “A global map of science based on the ISI subject categories”. Journal of the American Society for Information Science and Technology, v. 60, n. 2, pp. 348-362.
  • https://doi.org/10.1002/asi.20967
  • Limaymanta, César H. (2020). “El mapeo científico con VOSviewer: un ejemplo con datos de WoS”. Otlet. Revista para profesionales de información, n. 10. https://www.revistaotlet.com/tips-cesar-limaymanta-mapeo-cientifico-con-VOSviewer
  • Martínez-Nicolás, Manuel (2020). “La investigación sobre comunicación en España (1985-2015). Contexto institucional, comunidad académica y producción científica”. Revista latina de comunicación social, v. 75, pp. 383-414. https://doi.org/10.4185/RLCS-2020-1432
  • Moed, Henk F. (2020). “Appropriate use of metrics in research assessment of autonomous academic institutions”. Scholarly assessment reports, v. 2, n. 1, p. 1. https://doi.org/10.29024/sar.8
  • Moral-Muñoz, José A.; Herrera-Viedma, Enrique; Santisteban-Espejo, Antonio; Cobo, Manuel J. (2020). “Software tools for conducting bibliometric analysis in science: An up-to-date review”. El profesional de la información, v. 29, n. 1, e290103. https://doi.org/10.3145/epi.2020.ene.03
  • Moreno-Delgado, Alicia; Gorraiz, Juan; Repiso, Rafael (2021). “Assessing the publication output on country level in the research field communication using Garfield’s Impact Factor”. Scientometrics, v. 126, pp. 5983-6000. https://doi.org/10.1007/s11192-021-04006-w
  • Narin, Francis; Hamilton, Kimberly S. (1996). “Bibliometric performance measures”. Scientometrics, v. 36, pp. 293-310. https://doi.org/10.1007/BF02129596
  • Negroponte, Nicholas (2000). El mundo digital. Barcelona: Ediciones B.
  • Noyons, Ed C. M.; Moed, Henk F.; Van-Raan, Anthony F. J. (1999). “Integrating research performance analysis and science mapping”. Scientometrics, v. 46, pp. 591-604. https://doi.org/10.1007/BF02459614
  • Pickering, Bobby (2004). “Elsevier prepares Scopus to rival ISI Web of Science”. Information world review, v. 8.
  • Pritchard, Alan (1969). “Statistical bibliography or bibliometrics?”. Journal of documentation, v. 25, n. 4, pp. 348-349.
  • Salaverría, Ramón (2015). “Ideas para renovar la investigación sobre medios digitales”. El profesional de la Información, v. 24, n. 3, pp. 223-226. https://doi.org/10.3145/epi.2015.may.01
  • Schvaneveldt, Roger W. (ed.). (1990). Pathfinder associative networks. Westport: Ablex.
  • Schvaneveldt, Roger W.; Dearholt, Donald W.; Durso, Francis T. (1988). “Graph theoretic foundations of pathfinder networks”. Computers and mathematics with applications, n. 15, v. 4, pp. 337-345. https://doi.org/10.1016/0898-1221(88)90221-0 SCImago (2021a). SJ&CR – SCImago Journal & Country Rank. http://www.SCImagojr.com
  • SCImago (2021b). SIR – SCImago Institutions Rankings. http://www.SCImagoir.com
  • Skute, Igors; Zalewska-Kurek, Kasia; Hatak, Isabella; De-Weerd-Nederhof, Petra (2019). “Mapping the field: a bibliometric analysis of the literature on university-industry collaborations”. Journal of technology transfer, v. 44, n. 3, pp. 916-947. https://doi.org/10.1007/s10961-017-9637-1
  • Small, Henry (1999). “Visualizing science by citation mapping”. Journal of the American Society for Information Science, v. 50, n. 9, pp. 799-813. https://doi.org/10.1002/(SICI)1097-4571(1999)50:9<799::AID-ASI9>3.0.CO;2-G
  • Steensen, Steen (2011). “Online journalism and the promises of new technology”. Journalism studies, v. 12, n. 3, pp. 311-327. https://doi.org/10.1080/1461670X.2010.501151
  • Trabadela-Robles, Javier; Nuño-Moral, María-Victoria; Guerrero-Bote, Vicente P.; De-Moya-Anegón, Félix (2020). “Analysis of national scientific domains in the communication field (Scopus, 2003-2018)”. Profesional de la información, v. 29, n. 4, e290418. https://doi.org/10.3145/epi.2020.jul.18
  • Trillo-Domínguez, Magdalena (2008). Análisis cibermétrico de la prensa digital española. Ranking de calidad web y mapa de influencia mediática. Granada: Editorial Universidad de Granada.
  • Trillo-Domínguez, Magdalena; De-Moya-Anegón, Félix (2008). “Aproximación cienciométrica a la investigación en comunicación: el caso de Marshall McLuhan”. Profesional de la información, v. 17, n. 3, pp. 303-310. https://doi.org/10.3145/epi.2008.may.06
  • Van-Eck, Nees-Jan; Waltman, Ludo (2007). “Bibliometric mapping of the computational intelligence field”. International journal of uncertainty, fuzziness and knowledge-based systems, v. 15, n. 5, pp. 625-645. https://doi.org/10.1142/S0218488507004911
  • Van-Eck, Nees-Jan; Waltman, Ludo (2010). “Software survey: VOSviewer, a computer program for bibliometric mapping”. Scientometrics, v. 84, n. 2, pp. 523-538. https://doi.org/10.1007/s11192-009-0146-3
  • Van-Eck, Nees-Jan; Waltman, Ludo (2011). VOSviewer manual, https://www.VOSviewer.com/download/f-33t2.pdf
  • Van-Eck, Nees-Jan; Waltman, Ludo (2017). “Citation-based clustering of publications using CitNetExplorer and VOSviewer”. Scientometrics, v. 111, pp. 1053-1070. https://doi.org/10.1007/s11192-017-2300-7
  • Van-Eck, Nees-Jan; Waltman, Ludo; Van-den-Berg, Jan; Kaymak, Uzay (2006). “Visualizing the computational intelligence field”. IEEE Computational intelligence magazine, v. 1, n. 4, pp. 6-10. https://doi.org/10.1109/MCI.2006.329702
  • Van-Raan, Anthony F. J. (1999). “Advanced bibliometric methods for the evaluation of universities”. Scientometrics, v. 45, n. 3, pp. 417-423. https://doi.org/10.1007/BF02457601
  • Van-Raan, Anthony F. J. (2004). “Measuring science. Capita selecta of current main issues”. In: Moed, Henk F.; Glänzel, Wolfgang; Schmoch, Ulrich (eds.). Handbook of quantitative science and technology research: The use of publication and patent statistics in studies of s&t systems. Wolters Kluwer, pp. 19-50. ISBN: 1 4020 2702 8
  • Vargas-Quesada, Benjamín; De-Moya-Anegón, Félix (2007). Visualizing the structure of science. New York: Springer.
  • Velden, Theresa; Boyack, Kevin W.; Gläser, Jochen; Koopman, Rob; Scharnhorst, Andrea; Wang, Shenghui (2017).“Comparison of topic extraction approaches and their results”. Scientometrics, v. 111, n. 2, pp. 1169-1221. https://doi.org/10.1007/s11192-017-2306-1
  • White, Howard D. (2003). “Pathfinder networks and author cocitation analysis: A remapping of paradigmatic information scientists”. Journal of the American Society for Information Science and Technology, v. 54, n. 5, pp. 423-434. https://doi.org/10.1002/asi.10228