Trends in research related to the Dark Triad: A bibliometric analysis
The aim of this study was to investigate trends in research related to the Dark Triad using a bibliometric analysis. Four main clusters were recognized on author keywords: Dark Triad traits (Machiavellianism, narcissism, and psychopathy, along with terms such are life history theory, mating, and morality), measurement (short Dark Triad measures and terms related to psychometrics), personality models (Big Five, Five Factor Model, HEXACO, and terms related to sadism and aggression), and mainly gender differences cluster. The measurement and personality models clusters gathered the latest research, but specifically studies containing terms related to short Dark Triad measures and sadism. Analysis of the indexed keywords revealed a similar organization of the clusters, but with a great prominence of clinical studies and methodological terms. The map of bibliographic coupling showed several relatively separated groups of authors with different focus in cited references, with Jonason, P.K. in the central position. However, a map of co-citation of authors revealed closeness of these separated groups, with Jonason, P.K. and Paulhus, D.L. with nearly equal number of citations.
KeywordsDark Triad traits Life history strategy, short Dark Triad measures Personality models Gender differences Bibliometric analysis
This study was partially supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia [Grant ON179006].
Compliance with Ethical Standards
Conflict of Interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Authors state that the research meets all ethical requirements, and is adherent to the legal requirements of the Institutional Review Board which are in agreement with the Declaration of Helsinki.
- Boonroungrut, C., & Oo, T. (2017). Dark triad trends in personality studies: Systematic review with bibliometric network analysis. Journal of Humanity and Social Sciences Masharkham University, 36(6), 63–76.Google Scholar
- Chabrol, H., Van Leeuwen, N., Rodgers, R., & Séjourné, N. (2009). Contributions of psychopathic, narcissistic, Machiavellian, and sadistic personality traits to juvenile delinquency. Personality and Individual Differences, 47, 734–739. https://doi.org/10.1016/j.paid.2009.06.020.CrossRefGoogle Scholar
- D'Souza, M. F., & Jones, D. N. (2017). Taxonomy of the scientifc network of the dark triad: Revelations in the business and accounting context. Revista de Educação e Pesquisa em Contabilidade (REPeC) [Journal of Education and Research in Accounting], 11(3), 290–306. https://doi.org/10.17524/repec.v11i3.1588.Google Scholar
- Hodson, G., Hogg, S. M., & MacInnis, C. C. (2009). The role of “dark personalities” (narcissism, machiavellianism, psychopathy), big five personality factors, and ideology in explaining prejudice. Journal of Research in Personality, 43, 686–690. https://doi.org/10.1016/j.jrp.2009.02.005.CrossRefGoogle Scholar
- Jevremov, T. (2013). Razlike između mapa naučnih disciplina formiranih na osnovu koincidencije deskriptora nastalih kognitivnom obradom informacija i mapa proizvedenih primenom statističkih algoritama [differences between maps of scientific disciplines based on coincidence of descriptors generated by cognitive information processing and maps produced by using statistical algorithms]. Unpublished doctoral dissertation, University of Novi Sad, Serbia.Google Scholar
- Joshi, A. (2016). Comparison between SCOPUS & ISI web of science. Journal Global Values, 7(1), 1–11. Retrieved from http://anubooks.com/wp-content/uploads/2017/08/2016-7-JVG-No.-1-1.pdf. Accessed 15 Jan 2019.Google Scholar
- Karakus, M. (2018). Psychological capital research in social sciences: A bibliometric analysis. Electronic International Journal of Education, Arts, and Science (EIJEAS), 4(8), 39–58.Google Scholar
- Leydesdorff, L., & Zaal, R. (1988). Co-words and citations: Relations between document sets and environments. In L. Egghe & R. Rousseau (Eds.), Informetrics 87–88 (pp. 105–119). Amsterdam: Elsevier.Google Scholar
- Leydesdorff, L., & Rafols, I. (2012). Interactive overlays: A new method for generating global journal maps from web-of-science data. Journal of Informetrics, 6(2), 318–332. Retreived from https://arxiv.org/abs/1301.1013. Accessed 15 Jan 2019.
- Miller, J. D., Gaughan, E. T., Maples, J., & Price, J. (2011). A comparison of agreeableness scores from the big five inventoryand the NEO PI-R: Consequences for the study of narcissismand psychopathy. Assessment, 18, 335–339. https://doi.org/10.1177/1073191111411671.
- Murphy, L.S., Reinsch, S., Najm, W.I., Dickerson, V.M., Seffinger, M.A., Adams, A., & Mishra, S.I. (2003). Searching biomedical databases on complementary medicine: The use of controlled vocabulary among authors, indexers and investigators. BMC Complementary and Alternative Medicine, 3(3), 1–13. Published online 2003 Jul 7. https://doi.org/10.1186/1472-6882-3-3.
- Van Eck, N. J., & Waltman, L. (2014). Visualizing bibliometric networks. In Y. Ding, R. Rousseau, & D. Wolfram (Eds.), Measuring scholarly impact: Methods and practice (pp. 285–320). Switzerland: Springer.Google Scholar
- Zhao, D., & Strotmann, A. (2014). The knowledge base and research front of information science 2006–2010: An author cocitation and bibliographic coupling analysis. Journal of the Association for Information Science and Technology, 65(5), 995–1006. https://doi.org/10.1002/asi.23027.CrossRefGoogle Scholar