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

Kapitel i bok
Författare Danilo Garcia
Patricia Rosenberg
Sverker Sikström
Publicerad i Statistical Semantics - Methods and Applications
Förlag Springer
Publiceringsår 2019
Publicerad vid Psykologiska institutionen
Språk en
Ämnesord Dark Triad, Machiavellianism, Malevolent Character, Narcissism, Latent Semantic Algorithm, Psycholexical Hypothesis, Psychopathy, Quantitative Semantics.
Ämneskategorier Psykologi

Sammanfattning

Peoples’ tendencies to be manipulative, opportunistic, selfish, callous, and self-centered are reflected in individual differences in three dark traits: Machiavellianism, narcissism, and psychopathy. Research on this Dark Triad suggests lack of cooperation as a unified core among individuals who score high in these traits, but also that unique behaviors are salient depending on specific malevolent traits. However, there are mixed results on how the Dark Triad maps to other personality traits. Since personality is also expressed through self-descriptive language, our aim was to find a clearer distinction between people´s dark traits by investigating how people intentionally describe themselves. A total of 2,374 participants (845 men, 1,527 women), recruited from Amazon’s Mechanical Turk, responded to the Short Dark Triad and were also asked to generate ten self-descriptive words. 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) and profiles (i.e., three-dimensional analysis). The self-reported narcissism score was uniquely predicted by the semantic representations of narcissism (β = .77, p < .001). This was similarly for the self-reported psychopathy score (β = .68, p < .001); but not for the self-reported Machiavellianism score, which was predicted by all three semantic representations of the Dark Triad traits (Machiavellianism, β = .30, p < .001; narcissism β = -.12, p < .05; psychopathy β = .43, p < .001). 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 “out-going”. 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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