Leader Narcissism and Follower Engagement - A Machine Learning Approach

Gruda, Dritjon; Karanatsiou, Dimitra; Hanges, Paul J.; Goldbeck, Jennifer; Vakali, Athena

doi:10.5465/ambpp.2021.13307abstract

Cited by 2 publications

(2 citation statements)

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“…Linguistic-based text analytics or linguistic analytics exploits information about the syntax and semantics of a language as well as lexicons, to extract important information from textual data. For instance, while Gruda et al (2020) , Gruda, Karanatsiou, Mendhekar, Golbeck, & Vakali, (2021) , Gruda, Karanatsiou, Hanges, Goldbeck, & Vakali, (2021) , and Karanatsiou et al (2020) applied linguistic-based text analytics on Twitter data to detect traits such as narcissism and attachment, Ojo and Rizun (2019) employed linguistic markers found in negative free-text comments provided by hospital service users to determine the frequency and intensity of the associated negative experience. In addition, more recent work by Gruda and Ojo (2021) and Gruda, Ojo & Psychogios (2021) have also demonstrated that mental health signals can be identified from publicly available Twitter data.…”

Section: Methodsmentioning

confidence: 99%

All about that trait: Examining extraversion and state anxiety during the SARS-CoV-2 pandemic using a machine learning approach

Gruda

Ojo

2022

Personality and Individual Differences

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We examine the longitudinal relation between extraversion and state anxiety in a large cohort of New York City (NYC) residents using a linguistic analytical machine learning approach. Anxiety, both state and trait, and Big Five personality traits were predicted using micro-blog data on the Twitter platform. In total, we examined 1336 individuals and a total of 200,289 observations across 246 days. We find that before the onset of SARS-CoV-2 in NYC (before 1st March 2020), extraverts experienced lower state anxiety compared to introverted individuals, while this difference shrinks after the onset of the pandemic, which provides evidence that SARS-COV-2 is affecting all individuals regardless of their extraversion trait disposition. Secondly, a longitudinal examination of the presented data shows that extraversion seems to matter more greatly in the early days of the crisis and towards the end of our examined time range. We interpret results within the unique SARS-CoV-2 context and discuss the relationship between SARS-COV-2 and individual differences, namely personality traits. Finally, we discuss results and outline the limitations of our approach.

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Section: Methodsmentioning

confidence: 99%

All about that trait: Examining extraversion and state anxiety during the SARS-CoV-2 pandemic using a machine learning approach

Gruda

Ojo

2022

Personality and Individual Differences

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“…Prior research on the antecedents of leader emergence in traditional organizational settings has focused primarily on the Big Five personality traits (e.g., Cogliser et al, 2012;Ensari et al, 2011;Hu et al, 2019) or the dark triad traits (Gruda, Karanatsiou, et al, 2022;Gruda, Karanatsiou, Hanges, et al, 2021;Gruda, Karanatsiou, Mendhekar, et al, 2021). However, no previous studies have examined relational personality traits as antecedents of leader emergence in ad hoc teams.…”

Section: Introductionmentioning

confidence: 99%