Dinić, B.M., & Jevremov, T. (2019). Trends in research related to the Dark Triad: A
bibliometric analysis. Current Psychology. Manuscript accepted for publication.
Trends in research related to the Dark Triad: A bibliometric analysis
Running head: Trends in research related to the Dark Triad
Bojana M. Dinić and Tanja Jevremov
Department of Psychology, Faculty of Philosophy, University of Novi Sad, Serbia
This study was partially supported by the Ministry of Education, Science and Technological
Development of the Republic of Serbia [Grant ON179006].
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.
Keywords: Dark Triad traits; life history strategy, short Dark Triad measures; personality
models; gender differences; bibliometric analysis
The term Dark Triad was first used by Paulhus and Williams (2002) to describe a constellation of
three malevolent and socially toxic traits that could be found in a nonclinical population, such are
Machiavellianism, narcissism, and psychopathy. Machiavellianism refers to manipulative
interpersonal style, exploitation, and self-interest; narcissism is characterized by grandiosity,
entitlement, dominance, and superiority; while psychopathy is reflected in high impulsivity and
thrill-seeking along with low empathy and anxiety. Since then, there is growing literature and
extensive interest toward the Dark Triad (e.g., Furnham, Richards, & Paulhus, 2013). The Dark
Triad traits share some common characteristics and great effort has been invested in mapping the
core of these traits, including the exploration of its redundancy to some basic personality traits.
There are several proposals of the common core of these traits such arelife history strategy
(Jonason & Webster, 2010), callousness and manipulation (Jones & Figueredo, 2013),
disagreeableness (Miller et al., 2011), and dishonesty (Book, Visser, & Volk, 2015), but each of
the trait showed uniqueness in relations with different outcomes (e.g., Furnham et al., 2013).
The popularity of the Dark Triad was contributed to the development of two short measures:
Dark Triad Dirty Dozen (DTDD; Jonason & Webster, 2010) and Short Dark Triad (SD3; Jones &
Paulhus, 2014). However, each dark trait is multidimensional and some authors suggested that
research would benefit if main features of each trait were considered (e.g., Sleep, Lynam, Hyatt,
& Miller, 2017).
The expansion of research on the Dark Triad has resulted in the appearance of other candidates
for inclusion into the dark constellation. The most prominent is inclusion of everyday sadism,
which along with the other three dark traits constitutes the Dark Tetrad (Chabrol, Van Leeuwen,
Rodgers, & Séjourné, 2009). Marcus and Zeigler-Hill (2015) provide overviews of other traits
that could be included in the dark constellation, such are spitefulness, greed, perfectionism, and
dependency, while Hodson, Hogg, and MacInnis (2009) underline that social dominance also
shares the callous-manipulative core and serves as a candidate for dark trait. It could be
concluded that the nomological network of dark traits spreads and captures other related
constructs from the subclinical domain.
When a growing expansion is noted, bibliometric analysis is commonly used to illustrate the
scientific production and research trends (e.g., Karakus, 2018; Sa’ed, Sweileh, Awang, & Al-
Jabi, 2018). Bibliographic mapping is a set of bibliometric techniques that offers a visual
representation of a particular scientific area, which could provide a better insight into the main
research directions, relations among them, and their development. That kind of knowledge can
improve both scientific communication and information retrieval. In addition, a clearer
representation of prominent research topics and authors’ activities could be a useful tool in
science policy and research management (Rafols, Porter, & Leydesdorff, 2010).
However, in spite of the variety of research themes and trends, bibliometric analyses applied to
the Dark Triad field are relatively rare. Although there is a study that explored trends in Dark
Triad research focusing on a specific area (i.e., business and accounting, see D'Souza & Jones,
2017), there is a conspicuous lack of studies in which large datasets are used and trends are
explored regardless of research domain. To the best of our knowledge, there is only one study in
which a bibliometric approach was applied to documents from both Web of Science - WoS and
Google Scholar databases, with no limit regarding the year of publishing (from 1985 to 2016),
including articles, books, book chapters, conference papers, and doctoral dissertations
(Boonroungrut & Oo, 2017). The results of this analysis showed that titles and abstract keywords
extracted from analyzed documents related to dark personality could be classified into three
clusters: Dark Triad psychopathology, individual approach, and affect and response topics. The
authors pointed out that research focus had shifted from psychopathology (up to 2012) to
subclinical psychology and a variety of nonclinical areas, including management and financial
behavior (after 2012).
In this study, the exploration of research directions regarding dark traits involved several
additional analyses, as well as different samples of descriptors and documents which could be
more exhaustive and representative of the subject matter. Regarding the sample of descriptors,
the terms extracted from titles and abstracts used in previous research (Boonroungrut & Oo,
2017) often characterize a large degree of generality and the tendency that the same concept is
represented by different terms (Jevremov, 2013). Thus, in this study, the content of the
documents is represented by the types of keywords that could provide a more specific description
of the subject area – author keywords, and those that are controlled by thesauri – indexed
keywords. These two keyword types are meant to provide at least two distinct descriptions of the
documents. The first distinction between them is a higher level of standardization of indexed
terms, given that they are assigned to the records by a team of professional indexers according to
the corresponding controlled vocabularies (Joshi, 2016), while authors often use keywords that
are commonly understood and generally accepted, without consulting the thesauri (Rafferty &
Hidderly, 2007). The second difference refers to the content of the documents that they describe.
It can be assumed that indexed keywords offer descriptions based on the broader scientific
context depicted by the thesauri, while author keywords emphasize the actual content of a paper
and express what authors consider to be important keys to the article content (Jevremov, 2013;
Leydesdorff & Zaal, 1988). Previous research supported this distinction by finding low
consistency between authors and indexed keywords (e.g., Murphy et al., 2003). Because of this, it
is assumed that a more complete representation of the investigated area can be obtained by using
both keyword types and comparing the results they give.
In the case of the sample of documents, we used somewhat different sample than those used in
earlier research (Boonroungrut & Oo, 2017), in terms of the scientific database, publication type,
and selection criteria. First, we used documents from the Scopus database. It can be assumed that
the Scopus database would supply a more complete sample of documents than WoS because of
generally slightly better coverage of social sciences and humanities (Harzing & Alakangas,
2016), as well as more accurate data selection than Google Scholar because of better control over
the referred documents and the controlled indexing (Cecchino, 2010; Noruzi, 2005). Second, only
journal articles would be comprised in this analysis for at least two reasons. Firstly, unlike books
and book chapters, which generally provide an overview of previously obtained data, articles are
considered to be repositories of the latest empirical results and new knowledge. Therefore, they
are considered to be more adequate and accurate representations of the current research trends.
Secondly, in contrast to the majority of conference papers and book previews, articles contain
lists of references, which constitute data that are necessary for analyses based on citations.
Thirdly, it is assumed that the research trends in this area would be more correctly represented
and easily recognized if the analysis only focused on articles that are exclusively oriented
towards the Dark Triad or Dark Tetrad concepts. Thus, in order to obtain the most precise
selection of documents, the selection criteria should discriminate between articles related to all
dark traits and those related to only one particular dark trait.
Beside the keywords, in this research, the field of Dark Triad is represented by two additional
maps which were no previously explored. The first one is the map of bibliographic coupling
which represents the relations among authors based on their cited references. This map could
show different research groups and directions that form a research front in the Dark Triad
concept. The second one is the co-citation map of authors. This map could be a representation of
the base knowledge, which the actual researches share and rely on (Zhao & Strotmann, 2014). A
comparison of the authors' actual research activities and the authors’ recognition by their
contribution could offer a supplementary view on the dynamics in the Dark Triad field.
The concept of the Dark Triad has gained prominent popularity since its introduction, spreading
across different psychological disciplines. However, with the increasing popularity of the
concept, the worthwhile criticisms are also growing. Some of them pointed out the redundancy of
some members of the Dark Triad (e.g., Miller, Hyatt, Maples-Keller, Carter, & Lynam, 2016), or
its redundancy in relation to the personality trait related to antagonism (e.g., Vize, Lynam,
Collison, & Miller, 2016), while others pointed out methodological and psychometrical aspects of
treating the Dark Triad scores (e.g., Bertl, Pietschnig, Tran, Stieger, & Voracek, 2017) or
emphasized the need for multidimensionality of each dark trait (e.g., Sleep et al., 2017). At the
same time, the Dark Triad network is spreading and authors propose the inclusion of others traits
in this constellation (e.g., Marcus & Zeigler-Hill, 2015). Given the dynamic development of this
research area, the main aim of this study was to offer better insight into the research topics
associated with the Dark Triad by using the bibliometric analysis. Based on this analysis we
could map critical topics and domains of Dark Triad research, explore the amount of recognizing
the key problems related to Dark Triad research, as well as the lines of developments in this area.
In this analysis, two different samples of descriptors were used – author keywords and indexed
keywords. The results could thus present two different “perspectives” on the Dark Triad themes,
and reveal the main research direction, along with the new directions in this domain. The
additional aim was to investigate research trends and schools related to the Dark Triad,
represented by the authors’ coupling based on similarities of their papers’ references and as a
network of authors’ co-citations. The distinction between research groups may provide further
insight into main research directions regarding the dark traits and help to explore their possible
cohesion or distinction.
The sample of articles included 505 journal articles explicitly focusing on the dark traits, which
are referred in the Scopus database. All articles with “Dark Triad” OR “Dark Tetrad” terms
recognized in the title, abstract or keywords were selected. We collected information about their
descriptors, authors, references, the titles of the journals in which they were published and the
titles of the cited journals. The sample included articles published between the year of 2002,
when the term Dark Triad was introduced, and the end of 2018 year (see Figure 1).
Figure 1. Frequencies of published articles per year.
The articles were published in 150 journals. The most common source of Dark Triad citations
was journal Personality and Individual Differences (44% of articles), and then Journal of
Research in Personality (2.5%) and Current Psychology (2.5%). Personality and Individual
Differences was also the most-cited journal, with 20% of the total number of citations (3609
citations out of 18026 in total). However, several personality journals were also relatively
frequently cited, like Journal of Personality and Social Psychology (7%) and Journal of
Research in Personality (5%). The sample included 799 different author keywords and 420
different indexed keywords assigned by the Scopus procedure (Burnham, 2006). The articles
from the sample were published by 982 different authors and co-authors and cited by 17505
For investigation of the subject area of the Dark Triad, the bibliographic mapping technique was
applied. Research themes were visually represented by maps of term co-occurrences, based on
co-occurrences of descriptors of the articles. In this kind of map, descriptors that frequently occur
together in articles are placed close to one another on the map and potentially show a research
topic. Based on the type of descriptor used, two network maps of terms were calculated. In one
case, author keywords were used, and in the other, indexed keywords were employed. In the case
of author keywords, the most frequent term, “Dark Triad”, which was included in all articles, was
omitted in order to get a clear picture of term clusters. The same strategy was used in the case of
indexed keywords in order to enable comparison of the results.
Research trends and schools were represented by network maps which showed the relations
among authors. Firstly, a map of bibliographic coupling of authors was calculated. This kind of
map shows relations among authors based on the similarity of the documents they cite. In other
words, it shows similarity of the schools or the previous knowledge the authors rely on. Relations
among authors on this type of map are presented in such a way that the authors who cite the same
documents are placed beside each other on the map. Secondly, a map based on a co-citation
analysis of authors was calculated. This map illustrates the relations among cited authors based
on their coincidence in the references, so that the authors who are frequently cited together are
located close to one another on the map. Such a map can potentially reveal different directions in
the already settled and established knowledge, represented by its authors.
The bibliographic units were represented by circles and stronger relations among them were
marked with lines. The size of a circle was proportional to the number of articles associated with
a particular term or author, except in the case of the co-citation map, where the size of a circle
was proportional to the number of citations. The colors of the circles represented cluster
membership on the network maps. Additionally, the maps of terms were shown in overlay
versions (Leydesdorff & Rafols, 2012), where the colors of the circles represented the average
year of publication.
Data were analyzed and visually represented using VOSviewer v.1.6.10 software (Van Eck &
Waltman, 2014). All maps were constructed using a method that assigned the publication to each
bibliographic unit (term, cited document, and cited author) with a fractional weight (Perianes-
Rodriguez, Waltman, & Van Eck, 2016) and by applying lin-log modularity method for each
unit’s normalization (Noack, 2009; Van Eck & Waltman, 2009).
Selection of the bibliometric units that are to be represented on the map is one of the possible
flaws of the bibliometric mapping technique, since it could affect the map’s layout in terms of
ease of interpretation and precision of subject representation. Namely, a map that represents only
highly frequent units could underrepresent some important topics. Conversely, a map that
insufficiently represents frequent units could be unclear and less interpretable. To minimize
arbitrariness in this decision, we used several directions. Firstly, we followed the general
recommendations according to which the number and type of bibliometric units can be taken into
account (Klavans & Boyack, 2006). Accordingly, we set higher thresholds for cited authors than
for authors and keywords. Secondly, we conducted preliminary analyses in which we varied the
minimum thresholds for occurrences and chose solutions that showed robust results and
improved visibility of the main trends. Thirdly, the solutions that proved to be very inconsistent
with different methods of normalization and units’ associations were discarded. The map of
author keywords represented 44 terms and the map of indexed keywords represented 47 terms
that occurred in no fewer than five articles in the sample; the map of authors included 36 authors
who had more than five publications in the sample; and the co-citation map of authors included
395 authors with more than 20 citations. Apart from the maps, a list of the most cited documents
with the number of their citations was extracted.
The scientific landscape of main research areas related to dark traits is represented in Figure 2,
based on the author keywords in the co-occurrence map. Four main clusters could be recognized
in this network: 1. Dark Triad cluster, which includes the three main dark traits
(Machiavellianism, narcissism, and psychopathy) and terms related to life history theory (e.g.,
mating, morality); 2. measurement cluster, which mostly includes psychometrics terms and short
scales of the Dark Triad; 3. personality models cluster, which contains terms Big Five, Five
Factor Model, and HEXACO, along with terms referred to other dark traits candidate, such is
sadism, and terms referred to malevolent behaviors related to dark traits (e.g., aggression,
bullying, infidelity). 4. mainly gender differences cluster, with terms related to evolutionary
psychology, but also with terms of other personality traits related to lack of behavioral control
(impulsivity, sensation seeking). The fourth cluster seems to be the least cohesive, as it gathers
terms from different approaches. Besides these four clusters, there is also one small and very
narrow cluster, which comprises only two terms - dark personality and leadership. The terms that
are related to the latest publications are mostly in the second cluster, and related to short Dark
triad measures, and in the third cluster, and related to sadism and the Dark Tetrad (see Figure A
Figure 2. Map of co-occurrence of author keywords without term "Dark Triad".
In comparison to the author keywords map, the map based on indexed terms is formed of more
general terms. The structure of isolated clusters is generally the same as that obtained in the
author keywords. Two clusters are very similar: the Dark Triad and the measurement clusters, but
with emphasis of clinical construct related to psychopathy - antisocial personality disorder.
However, the other two clusters favor age characteristics of the sample as the used research
method. Thus, one cluster gathers terms that refer to clinical studies, experimental studies,
behavioral research, and adult or student sample. Among non-methodological terms there are
sadism, aggression, impulsivity, morality. The terms in this cluster belongs to the newest
publications (see Figure B in Supplement). The other cluster gathers terms that refer to
personality tests, genetics and physiology, and samples other than students and adults (such are
younger or older samples, see Figure 3). In this cluster, terms related to physiology belong to the
Figure 3. Map of co-occurrence of indexed keywords without term "Dark Triad".
The map based on bibliographic coupling of authors shows several relatively distinct groups of
authors that represent different directions in the area of dark trait research (Figure 4). The central
group with the largest number of papers (over 40%) is clustered around Jonason, P.K., the second
group is clustered around Jones, D.N./Paulhus, D.L., and the third group is clustered around
Vernon, P.A. Considering the number of links toward the central position, it seems that a part of
the cited documents in other/smaller groups is similar to those in Jonason’s group. The group
around Miller, J.D, Lynam, D.R., and Campbell, W.K. appeared to be distinct from the others.
We further explore the author keywords in obtained groups. Despites three key terms regarding
the Dark Triad, terms such as gender differences, Big Five, evolutionary psychology, life history
theory, mating, and DTDD prevail in the Jonason, P.K. group; in the Jones, D.N./Paulhus, D.L.
group, terms such as sadism, Dark Tetrad, HEXACO, and aggression are prevalent; in the
Vernon P.A. group, terms such as behavioral genetics, twin study, deception, and evolutionary
psychology are prevalent; while in the Miller, J.D. group, we observed a prevalence of terms
related to psychometrics (e.g., validity, assessment, and confirmatory factor analysis), the Big
Five, the Five Factor Model, and gender differences (see Table A in Supplement).
Figure 4. Map of bibliographic coupling of authors.
Unlike the domain of bibliographic coupling of authors where one dominant author is recognized
(Jonason, P.K.), the reference domain of cited authors is more balanced (Figure 5). Namely,
Paulhus, D.L. (1708 citations) has nearly as many citations as Jonason, P.K. (1716 citations).
These two most-cited authors are followed by Jones, D.N., Webster, G.D., Hare, R., Williams,
K.M., and Miller, J.D. (with 903, 630, 605, 567, and 550 citations, respectively).
Figure 5. Map of co-citation analysis of authors.
The list of the most-cited documents reveals the key articles for the main directions recognized in
the authors’ co-citation map (Table B in Appendix): one direction is gathering around Paulhus
and Williams (2002) article (cited 1013 times in this sample), and others mostly include Jonason,
P.K. research groups' articles with the centrality of Jonason and Webster (2010) article on the
Dark Triad Dirty Dozen instrument (cited 304 times in this sample).
Ever since the term Dark Triad was introduced mere 17 years ago, interest in the Dark Triad
constellation has been rapidly growing, but criticisms of this construct were also made. In this
study we focused on the scientific production and main research trends regarding the Dark Triad
and other recognized dark traits. The selected 505 journal articles were analyzed in terms of the
main and underlying themes, cited references and authors.
Results of the co-occurrence of author keywords showed that different research directions could
be recognized. These directions formed four main clusters. The first cluster contained the three
main dark traits along with evolutionary-based life history theory. Thus, the main author in this
area (Jonason, P.K.) suggested that the common element, that is, the “core” of the Dark Triad was
a fast and exploitive life history strategy (Jonason & Webster, 2010).
The second cluster contained the terms that referred to the psychometric approach and covered
topics regarding validity, reliability, and other related terms/concepts, as well as the two short
instruments of the Dark Triad (DTDD and SD3). This cluster also included terms such are
empathy, emotional intelligence, and revenge, which are common constructs outside the basic
personality traits in determining the validity of dark traits instruments. The newest terms in these
clusters mostly originated from the short Dark Triad measures, indicating the research trend
related to the cross-cultural validation of these instruments.
The third cluster represented the research perspective focused mostly on the basic personality
models, such as the Big Five Model, the Five Factor Model, and the HEXACO model, with an
emphasis on the traits that are mostly related to dark traits - Agreeableness and Honesty-
Humility. There are active lines of research about the “core” of the dark traits, which could be
linked to the basic personality traits. One group of authors suggested that the “core” of the Dark
Triad is Agreeableness (e.g., Miller et al., 2010; Vize et al., 2016), while due to the popularity of
the HEXACO model, another group suggested that Honesty-Humility may be the best candidate
for the explanation of the shared characteristics of the members of the Dark Triad (e.g., Book et
al., 2015, 2016). In line with the novelty of research on dark traits, this cluster also included other
members of dark traits, for instance, sadism. Sadism refers to the tendency towards intentionally
hurting others for pleasure or asserting dominance (e.g., O'Meara, Davies, & Hammond, 2011),
and it is related to aggressive behavior, bullying, internet trolling, and the like (e.g., Buckles,
Trapnell, & Paulhus, 2014). This line of the research regarding sadism and its behavioral
indicators was also recognized as newer.
The fourth cluster is the least cohesive, with the domination of terms such are gender differences,
evolutionary psychology, and deception, which could point to the evolutionary psychology
approach. Although some aspects of evolutionary psychology are included in the first cluster, the
results showed a clear distinction between life history theory and evolutionary theory, in general.
In this cluster, there are also terms related to personality traits that refer to a lack of behavioral
control (impulsivity, sensation-seeking), which is also often explored from the standpoint of
evolutionary psychology, along with gender differences. In general, it could be noted that two
clusters, the Dark Triad and the personality models, were similar to those found in previous
bibliometric study (Boonroungrut & Oo, 2017), while the clusters newly recognized in this study
were the measurement and the gender difference.
The map based on indexed keyword showed a similar picture, with recognizing the Dark Triad
and the measurement clusters. The difference between author and indexed keywords lies in the
fact that indexed keywords include more general terms, which is why terms that refer to sample
age and study method are more frequently found in the indexed keywords map. This result is a
possible consequence of the method of indexing in Scopus, which uses thesauri that covers
medicine and life sciences better than social sciences (Burnham, 2006). Thus, a cluster with
clinical, experimental, and behavior studies was recognized, with adults and students as the most
frequent sample, and this cluster gathered the newest publications. The other cluster included
studies conducted on non-student and non-adult samples (e.g., youth and elderly), with focus on
personality tests, genetics, and risk factors. It could be noticed that clinical studies and topics
were more visible compared to other psychological disciplines recognized on authors keywords
(e.g., evolutionary psychology). Thus, it seems that the trend of clinical research regarding the
Dark Triad is still sustainable, which is in line with the results of the previous study
(Boonroungrut & Oo, 2017).
This result suggests that author and indexed keywords are to some extent complementary and that
using both of them can improve article description and, consequently, their visibility in
The structure of clusters based on authors and indexed keywords highlights critical topic
regarding dark traits research, and we could conclude that amount of research were mostly
focused on explanation of Dark Triad in the context of evolutionary theories or personality
models, or on cross-cultural validation of Dark Triad measurements. It should be noticed that
measurement cluster was not recognized in previous study (Boonroungrut & Oo, 2017) and
clearly represent the trend in Dark Triad research. In line with Furnham et al. (2010), areas of
mating, interpersonal and antisocial behavior are recognized. Area of clinical research is also
recognized, but we could notice that the structure of this area is different from previous study
(Boonroungrut & Oo, 2017) and that do not include terms related to mental disorders. Moreover,
clinical area is still active and gathering the newest publications. However, some areas of the
Dark Triad research were not clearly recognized (i.e., occupational psychology) compared to the
results of previous study (Boonroungrut & Oo, 2017).
Furthermore, some solutions of the concerns regarding Dark Triad research were recognized in
organization of indexed keywords, such are use of different methodological approaches and non-
convenience sample. This line of research represents the newest studies, and we could conclude
that authors recognize the need for multimethod approach and diversity of sampling approach.
However, other problems such are redundancy of dark traits, treatment of dark traits as
unidimensional, and statistical treatment of dark traits in multivariate approach, were not
recognized in obtained clusters. Thus, seems that authors invested in cross-cultural validity of
Dark Triad measurements and possibility to reduce Dark Triad on some basic trait or
evolutionary concept, while answers on other fundamental questions about status of each dark
trait were not recognized.
The map of bibliographic coupling showed that several research directions or schools could be
differentiated, with Jonason, P.K. in the center, which suggested that there was a partial similarity
in cited references among all authors, similar to those cited by Jonason, P.K. Apart from Jonason,
P.K. group, other author groups were recognized, such as the groups around Vernon, P.A., Jones,
D.N./Paulhus, D.L., and Miller, J.D. Analysis of keywords in each group suggested different
focus. For example, the Jonason, P.K. group mostly focused on life history and evolutionary
theory, gender differences, and mating, which suggested one direction of study of the dark traits.
On the other hand, the Vernon, P.A. group mostly focused on behavioral genetics, which
emphasizes the biological line of the dark traits research. The group around Jones, D.N./Paulhus,
D.L. mostly focused on sadism as the fourth member of the dark traits and malevolent behaviors,
such as aggression. The most distinct was the group around Miler, J.D., which mostly focused on
psychometric topics but also on the clinical perspective regarding the dark traits. It could be
noticed that the main criticism of the Dark Triad construct, its measures, and treatment of scores
comes from this group of authors (e.g., Miller et al., 2010; Vize et al, 2016). Thus, although very
similar base knowledge shared by each research group, each group have focus on different
research line towards dark traits. Future researcher should be aware of these authors groups in
exploring the topics of Dark Triad.
However, the map of co-citation analysis of authors seems more balanced and clearly indicates
two most-cited authors in this area, Jonason, P.K. and Paulhus, D.L., who are also among authors
of two short measures of the Dark Triad. This result reveals that while in the actual studies there
is a high level of concentration on one author, the knowledge base is characterized by greater
This study has several limitations. Firstly, the selected sample of documents reflects the
characteristics of the articles published in journals referred in the Scopus database and focuses on
the researchers of main dark traits taken together. Although such a sample was intentionally
selected, samples extracted from other databases could possibly yield different conclusions about
this scientific field. Secondly, like most visualization techniques, the technique we used suffers
from partial arbitrariness regarding the chosen method for setting the thresholds, weighting and
normalization. Although we opted for solutions that are generally recommended (Klavans &
Boyack, 2006; Perianes-Rodriguez, Waltman, & Van Eck, 2016) and showed robustness across
units’ associations and types of normalizations in this sample of data, these specificities could
affect the results.
In summary, the results of this study provide insight into new trends in the field of the Dark
Triad, suggesting the spread of Dark Triad network on other candidates, exploration of an
extended list of outcomes, and diversity of methodological approaches. Moreover, the results
provide useful information regarding the relatively distinct research groups in the study of the
dark traits, focusing on the evolutionary, genetic, or clinical perspective. The benefits of these
results for future authors would be to highlight the critical research themes and lines in study of
dark traits, as well as recognition of insufficiently investigated topics and issues which could be a
basis for future studies.
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
Ashton, M.C., & Lee, K. (2007). Empirical, theoretical, and practical advantages of the
HEXACO model of personality structure. Personality and Social Psychology Review, 11,
Bertl, B., Pietschnig, J., Tran, U.S., Stieger, S., & Voracek, M. (2017). More or less than the sum
of its parts? Mapping the Dark Triad of personality onto a single Dark Core. Personality
and Individual Differences, 114, 140–144. https://doi.org/10.1016/j.paid.2017.04.002
Book, A., Visser, B.A., Blais, J., Hosker-Field, A., Methot-Jones, T., Gauthier, N.Y., ...&
D'Agata, M.T. (2016). Unpacking more “evil”: What is at the core of the dark tetrad?
Personality and Individual Differences, 90, 269–272.
Book, A., Visser, B.A., & Volk, A.A. (2015). Unpacking “evil”: Claiming the core of the Dark
Triad. Personality and Individual Differences, 73, 29–38.
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.
Buckels, E.E., Trapnell, P.D., & Paulhus, D.L. (2014). Trolls just want to have fun. Personality
and Individual Differences, 67, 97–102. https://doi.org/10.1016/j.paid.2014.01.016
Burnham, J.F. (2006). Scopus database: A review. Biomedical digital libraries, 3(1), 1–8.
Cecchino, N.J. (2010). Google scholar. Journal of the Medical Library Association, 98(4), 320–
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.
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–
Furnham, A., Richards, S.C, & Paulhus, D.L. (2013). The Dark Triad of personality: A 10 year
review. Social and Personality Psychology Compass, 7(3), 199–216.
Harzing, A.W., & Alakangas, S. (2016). Google Scholar, Scopus and the Web of Science: A
longitudinal and cross-disciplinary comparison. Scientometrics, 106(2), 787–804.
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.
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.
Jonason, P.K., & Webster, G.D. (2010). The Dirty Dozen: A concise measure of the Dark Triad.
Psychological Assessment, 22(2), 420–432. http://dx.doi.org/10.1037/a0019265
Jones, D.N., & Figueredo, A.J. (2013). The core of darkness: Uncovering the heart of the Dark
Triad. European Journal of Personality, 27, 521–531. https://doi.org/10.1002/per.1893
Jones, D. N., & Paulhus, D. L. (2014). Introducing the Short Dark Triad (SD3): A brief measure
of dark personality trait. Assessment, 21(1), 28–41.
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-
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.
Klavans, R. & Boyack, K.W. (2006). Quantitative evaluation of large maps of science.
Scientometrics, 68(3), 475-499. https://doi.org/10.1007/s11192-006-0125-x
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
Leydesdorff, L., i 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).
Marcus, D.K., & Zeigler-Hill, V. (2015). A big tent of dark personality traits. Social and
Personality Psychology Compass, 9(8), 434–446. https://doi.org/10.1111/spc3.12185
Miller, J.D., Hyatt, C.S., Maples-Keller, J.L., Carter, N.T., & Lynam, D.R. (2016). Psychopathy
and Machiavellianism: A distinction without a difference? Journal of Personality, 85(4),
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
Noack, A. (2009). Modularity clustering is force-directed layout. Physical review. E, Statistical,
Nonlinear, and Soft Matter Physics, 79(2 Pt 2), 026102.
Noruzi, A. (2005). Google Scholar: The new generation of citation indexes, Libri, 55(4), 170–
180. Retrieved from http://hdl.handle.net/10760/7179
O’Meara, A., Davies, J., & Hammond, S. (2011). The psychometric properties and utility of the
Short Sadistic Impulse Scale (SSIS). Psychological Assessment, 23, 523–531.
Paulhus, D.L, & Williams, K.M. (2002). The Dark Triad of Personality: Narcissism,
Machiavellianism, and Psychopathy. Journal of Research in Personality, 36(6), 556–563.
Perianes-Rodriguez, A., Waltman, L., & Van Eck, N.J. (2016). Constructing bibliometric
networks: A comparison between full and fractional counting. Journal of Informetrics,
10(4), 1178–1195. https://doi.org/10.1016/j.joi.2016.10.006
Rafferty, P., & Hidderly, R. (2007). Flickr and Democratic Indexing: Dialog approaches to
indexing. Aslib Proceedings: New Information Perspectives, 59(4/5), 397–410.
Rafols, I., Porter, A.L., & Leydesdorff, L. (2010). Science overlay maps: A new tool for research
policy and library management. Journal of the American Society for information Science
and Technology, 61(9), 1871–1887.
Sa’ed, H.Z., Sweileh, W.M., Awang, R., & Al-Jabi, S.W. (2018). Global trends in research
related to social media in psychology: mapping and bibliometric analysis. International
Journal of Mental Health Systems, 12, 4. https://doi.org/10.1186/s13033-018-0182-6
Sleep, C.E., Lynam, D.R., Hyatt, C.S., & Miller, J.D. (2017). Perils of partialing redux: The case
of the Dark Triad. Journal of Abnormal Psychology, 126, 939–950.
Van Eck, N.J., & Waltman, L. (2009). How to normalize cooccurrence data? An analysis of some
well-known similarity measures. Journal of the American Society for Information Science
and Technology, 60(8), 1635–1651. https://doi.org/10.1002/asi.21075
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.
Vize, C.E., Lynam, D.R., Collison, K.L., & Miller, J.D. (2016). Differences among dark triad
components: A meta–analytic investigation. Personality disorders: Theory, research, and
treatment, 9(2), 101–111. http://dx.doi.org/10.1037/per0000222.
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.
Figure A. Map of co-occurrence of author keywords without term "Dark Triad", colored by
average publication year.
Figure B. Map of co-occurrence of indexed keywords without term "Dark Triad", colored by
average publication year.
The most frequent authors keywords in authors groups
dark triad (91)
dark triad (64)
dark triad (23)
dark triad (12)
behavior genetics (6)
big five (8)
big five (2)
dark tetrad (7)
twin study (3)
life history theory (6)
antisocial behavior (2)
five factor model (2)
dark triad dirty dozen
big five (5)
gender differences (2)
gender differences (2)
video games (4)
facial morphs (4)
dark personality (3)
age differences (1)
big five (1)
Note. Weight occurrences are in the parenthesis.
The most cited articles
Paulhus, D.L., & Williams, K.M. (2002). The Dark Triad of personality:
Narcissism, Machiavellianism, and psychopathy. Journal of Research in
Personality, 36, 556–563.
Jonason, P.K., & Webster, G.D. (2010). The Dirty Dozen: A concise measure of
the Dark Triad. Psychological Assessment, 22, 420–432.
Lee, K., & Ashton, M.C. (2005). Psychopathy, Machiavellianism, and Narcissism
in the Five-Factor model and the HEXACO model of personality structure.
Personality and Individual Differences, 38, 1571–1582.
Furnham, A., Richards, S.C., & Paulhus, D.L. (2013). The Dark Triad of
personality: A 10 year review. Social and Personality Psychology Compass, 7,
Jakobwitz, S., & Egan, V. (2006). The Dark Triad and normal personality traits.
Personality and individual differences, 40, 331–339.
Jones, D.N., & Paulhus, D.L. (2014). Introducing the Short Dark Triad (SD3): A
brief measure of dark personality traits. Assessment, 21, 28–41.
O'Boyle, E.H.Jr., Forsyth, D.R., Banks, G.C., & McDaniel, M.A (2012). A meta-
analysis of the dark triad and work behavior: A social exchange perspective.
Journal of Applied Psychology, 97, 557–579.