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Dark Identity: Distinction between Malevolent Character Traits through Self-descriptive Language

Kapitel i bok
Författare Danilo Garcia
Patricia Rosenberg
Franco Lucchese
Anna Sahlström
Sverker Sikström
Publicerad i Statistical Semantics - Methods and Applications. Sikström, Sverker, Garcia, Danilo (Eds.)
Förlag Springer
Publiceringsår 2020
Publicerad vid Psykologiska institutionen
Språk en
Ämnesord Dark Triad, Machiavellianism, Malevolent Character, Narcissism, Latent Semantic Algorithm, Psycholexical Hypothesis, Psychopathy, Quantitative Semantics.
Ämneskategorier Psykologi


Peoples’ tendencies to be manipulative, opportunistic, selfish, callous, amoral, and self-centered (i.e., an outlook of separateness; Cloninger 2004, 2007, 2013) are reflected in individual differences in three dark traits: Machiavellianism, narcissism, and psychopathy (Paulhus and Williams 2002). At a general level, individuals who express any of these dark traits also express uncooperativeness as one common aspect of their vicious character (cf. Garcia and Rosenberg 2016). In addition, people who express different levels of each of these malevolent traits, also express different levels of extraversion, conscientiousness, neuroticism and other personality tendencies (cf. Vernon et al. 2008). However, these associations are inconsistent across samples (Garcia and Rosenberg 2016). What is even more, besides temperament and character traits, the concept of the self and a person’s identity is also expressed when individuals intentionally describe themselves (see Chap. 8); some might describe themselves as talkative, others as shy, goal-directed, manipulative, kind, loving, and etcetera. The question is, if the words people use to describe themselves express their malevolent character? In other words, is the meaning of these words related to their dark tendencies? Our aim was to find a clearer distinction between people’s dark tendencies by investigating the relationship between how people intentionally describe themselves and their self-reported malevolent character traits. In the first analysis, we quantified the self-descriptive words to represent the semantic meaning of each malevolent character trait using the Latent Semantic Algorithm. These semantic representations of malevolent character where then used to predict the self-reported scores of the Dark Triad. The second set of analyses were word-frequency analyses that mapped the self-descriptive words to individuals’ self-reported malevolent character traits scores (i.e., one-dimension analysis; see Garcia and Sikström, 2019) and profiles (i.e., three-dimensional analysis; see Garcia et al. 2020). The self-reported narcissism score was uniquely predicted by the semantic representations of narcissism. This was similarly for the self-reported psychopathy score; but not for the self-reported Machiavellianism score, which was predicted by all three semantic representations of the Dark Triad traits. At the one-dimension level, the word “sarcastic” differentiated individuals with Machiavellian tendencies, “mean” was indicative of high psychopathy and finally narcissistic tendencies were differentiated by self-descriptive words such as “leader” and “outgoing”. People low in Machiavellianism and psychopathy were both unified by self-presentations such as “kind” and “caring”, whereas people low in narcissism indicated by self-descriptions such as “shy” or “introvert”. At the three-dimensional level, profiles gave more nuanced findings suggesting specific keywords that unify or that make the dark traits unique. Hence, we suggest that self-descriptive words, alongside the computational methods and the profiling approach used here, may complement traditional methods for the identification of a person’s dark identity, which seems to be an explicit and aware part of the self.

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