Four personality types may be neither robust nor exhaustive

Freudenstein, Jan‐Philipp; Strauch, Christoph; Mussel, Patrick; Ziegler, Matthias

doi:10.1038/s41562-019-0721-4

Cited by 21 publications

(20 citation statements)

References 8 publications

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“…Our discussion is closely related to another commentary on Gerlach et al (2018) by Freudenstein et al (2019). By reanalyzing the Johnson-300 data set (Johnson, 2014), Freudenstein et al (2019) pointed out that only less than half (42%) of the respondents was classified into four meaningful clusters. The mechanism that we suggested provides a natural explanation to this result.…”

Section: Procedures Of Analysis and Its Pitfallsupporting

confidence: 54%

Commentary: A robust data-driven approach identifies four personality types across four large data sets

et al. 2020

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Section: Procedures Of Analysis and Its Pitfallsupporting

confidence: 54%

Commentary: A robust data-driven approach identifies four personality types across four large data sets

et al. 2020

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“…Permission for the use of this database was obtained in 2018, and Ethical Approval for this piece of secondary data analysis was obtained from the Ethics Committee of the School of Informatics, University of Edinburgh. Other publications using this dataset include [22,49].…”

Section: Datamentioning

confidence: 99%

“…Radloff [39] proposed three groups of depression severity: low (0-15), mild to moderate (16)(17)(18)(19)(20)(21)(22), and high . For using mood profile to predict self-reported depressive symptoms, we followed the practice from previous social media studies [18,36,41,53] and adopted 22 as a cutoff point to divide participants into high symptoms and low symptom groups.…”

Section: Screening For Depressive Symptomsmentioning

confidence: 99%

Examining the Role of Mood Patterns in Predicting Self-Reported Depressive symptoms

Chen

Magdy

Whalley

et al. 2020

12th ACM Conference on Web Science

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Researchers have explored automatic screening models as a quick way to identify potential risks of developing depressive symptoms. Most existing models include a person's mood as reflected on social media at a single point in time as one of the predictive variables. In this paper, we study the changes and transition in mood reflected on social media text over a period of one year using a mood profile. We used a subset of the "MyPersonality" Facebook data set that comprises users who have consented to and completed an assessment of depressive symptoms. The subset consists of 93,378 Facebook posts from 781 users. We observed less evidence of mood fluctuation expressed in social media text from those with low symptom measures compared to others with high symptom scores. Next, we leveraged a daily mood representation in Hidden Markov Models to determine its associations with subsequent self-reported symptoms. We found that individuals who have specific mood patterns are highly likely to have reported high depressive symptoms. However, not all of the high symptoms individuals necessarily displayed this characteristic, which indicates presence of potential subgroups driving these findings. Finally, we leveraged multiple mood representations to characterize levels of depressive symptoms with a logistic regression model. Our findings support the claim that for some people, derived mood from social media text can be a proxy of real-life mood, in particular depressive symptoms. Combining the mood representations with other proxy signals can potentially advance responsibly used semi-automatic screening procedures.

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“…The typological approach has a long history in psychology and is aimed at providing information about differences between individuals by summarizing their expression on several independent characteristics. The advantages and disadvantages of the typological approach have been the subject of critical discussion in recent decades (Bergman & Trost, 2006; Meehl, 1992; Robins, John, & Caspi, 1998), and this approach has been rejected in order to make important decisions about individuals in practice (Freudenstein, Strauch, Mussel, & Ziegler, 2019). Nevertheless, typological approaches have been employed in contemporary personality research (e.g.…”

Section: The Present Studymentioning

confidence: 99%

Personality in Action: Assessing Personality to Identify an ‘Ideal’ Conscientious Response Type with Two Different Behavioural Tasks

2020

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Performance on achievement tests is characterized by an interplay of different individual attributes such as personality traits, motivation or cognitive styles. However, the prediction of individuals' performance from classical self‐report personality measures obtained during large and comprehensive aptitude assessments is biased by, for example, subjective response tendencies. This study goes beyond by using behavioural data based on two different types of tasks, requiring different conscientious‐related response behaviours. Moreover, a typological approach is proposed, which includes different behavioural indicators to obtain information on complex personality characteristics. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology

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Four personality types may be neither robust nor exhaustive

Cited by 21 publications

References 8 publications

Commentary: A robust data-driven approach identifies four personality types across four large data sets

Commentary: A robust data-driven approach identifies four personality types across four large data sets

Examining the Role of Mood Patterns in Predicting Self-Reported Depressive symptoms

Personality in Action: Assessing Personality to Identify an ‘Ideal’ Conscientious Response Type with Two Different Behavioural Tasks

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