Personality perception: A developmental study

McLarney-Vesotski, Amber; Bernieri, Frank J.; Rempala, Daniel M.

doi:10.1016/j.jrp.2005.07.001

Cited by 19 publications

(16 citation statements)

References 30 publications

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“…Automatically identifying the author's personality in a corpus could also improve language generation, as individual differences in language affect the way that concepts are expressed (Reiter & Sripada, 2004). Studies have also shown that users' evaluation of conversational agents depends on their own personality (Reeves & Nass, 1996;Cassell & Bickmore, 2003), which suggests a requirement for such systems to adapt to the user's personality, like humans do (Funder & Sneed, 1993;McLarney-Vesotski, Bernieri, & Rempala, 2006). While in some applications it would be possible to acquire personality information by asking the user or author directly (John, Donahue, & Kentle, 1991;Costa & McCrae, 1992), here we explore whether it is possible to acquire personality models for the Big Five personality traits by observation of individual linguistic outputs in text and conversation.…”

Section: Introductionmentioning

confidence: 99%

Using Linguistic Cues for the Automatic Recognition of Personality in Conversation and Text

Mairesse¹,

Walker²,

Mehl³

et al. 2007

jair

746

583

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It is well known that utterances convey a great deal of information about the speaker in addition to their semantic content. One such type of information consists of cues to the speaker's personality traits, the most fundamental dimension of variation between humans. Recent work explores the automatic detection of other types of pragmatic variation in text and conversation, such as emotion, deception, speaker charisma, dominance, point of view, subjectivity, opinion and sentiment. Personality affects these other aspects of linguistic production, and thus personality recognition may be useful for these tasks, in addition to many other potential applications. However, to date, there is little work on the automatic recognition of personality traits. This article reports experimental results for recognition of all Big Five personality traits, in both conversation and text, utilising both self and observer ratings of personality. While other work reports classification results, we experiment with classification, regression and ranking models. For each model, we analyse the effect of different feature sets on accuracy. Results show that for some traits, any type of statistical model performs significantly better than the baseline, but ranking models perform best overall. We also present an experiment suggesting that ranking models are more accurate than multi-class classifiers for modelling personality. In addition, recognition models trained on observed personality perform better than models trained using selfreports, and the optimal feature set depends on the personality trait. A qualitative analysis of the learned models confirms previous findings linking language and personality, while revealing many new linguistic markers.

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Section: Introductionmentioning

confidence: 99%

Using Linguistic Cues for the Automatic Recognition of Personality in Conversation and Text

Mairesse¹,

Walker²,

Mehl³

et al. 2007

jair

746

583

View full text Add to dashboard Cite

show abstract

“…A large volume of research has already investigated whether or not various traits are perceptible (Albright, Kenny, & Malloy, 1988;Borkenau & Liebler, 1993;Borkenau, Mauer, Riemann, Spinath, & Angleitner, 2004;Carney, Colvin, & Hall, 2007;Funder, Kolar, & Blackman, 1995;McLarney-Vesotski, Bernieri, & Rempala, 2006;Thoresen, Vuong, & Atkinson, 2012;Todorov, Pakrashi, & Oosterhof, 2009), but the current research has a slightly different purpose. Past research only tells us that people (henceforth 'perceivers') can systematically infer personality traits; it does not tell us whether people can more easily infer who is at the extremes compared with who is in the middle of a continuum.…”

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confidence: 99%

Being Sherlock Holmes: Can we sense empathy from a brief sample of behaviour?

Sheppard

Mitchell

2015

British J of Psychology

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Mentalising (otherwise known as 'theory of mind') involves a special process that is adapted for predicting and explaining the behavior of others (targets) based on inferences about targets' beliefs and character. The current research investigated how well participants made inferences about an especially apposite aspect of character, empathy. Participants were invited to make inferences of self-rated empathy after watching or listening to an unfamiliar target for a few seconds telling a scripted joke (or answering questions about him/herself or reading aloud a paragraph of promotional material). Across three studies participants were good at identifying targets with low and high self-rated empathy but not good at identifying those who are average. Such inferences, especially of high self-rated empathy, seemed to be based mainly on clues in the target's behavior, presented either in a video, a still photograph or in an audio track. However, participants were not as effective in guessing which targets had low or average self-rated empathy from a still photograph showing a neutral pose or from an audio track. We conclude with discussion of the scope and the adaptive value of this inferential ability.

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“…Previous research suggests that people are capable of making accurate judgments about some dimensions of the big‐five traits (e.g. Albright et al, ; Borkenau & Liebler, , ; Borkenau et al, ; Carney et al, ; McLarney‐Vesotski et al, ; Watson, ) and can detect the distinctive from the normal in terms of general personality profiles (Biesanz & Human, ). The present study has extended these findings by showing that when people judge targets as being at the outer levels (high or low) of the big‐five personality continua, they tend to be correct, while this is not the case when they judge targets to be in the middle.…”

Section: Discussionmentioning

confidence: 99%

“…Research has already investigated whether or not various traits are perceptible (e.g. Albright, Kenny, & Malloy, ; Back & Nestler, ; Borkenau & Liebler, , ; Borkenau, Mauer, Riemann, Spinath, & Angleitner, ; Carney et al, ; Funder, ; Funder, Kolar, & Blackman, ; Kenny, Horner, Kashy, & Chu, ; McLarney‐Vesotski, Bernieri, & Rempala, ; Thoresen et al, ; Todorov, Pakrashi, & Oosterhof, ), but the current research has a slightly different purpose. Past research usually tells us that people (henceforth ‘perceivers’) can systematically infer some aspects of personality traits; it does not tell us whether people's judgments differ at differing levels of a trait continuum.…”

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confidence: 99%

“…Borkenau & Liebler, ; Borkenau et al, ; Carney et al, ; McLarney‐Vesotski et al, ; Norman & Goldberg, ; Wall, Taylor, Dixon, Conchie, & Ellis, ; Watson, ). For instance, in the study by Borkenau et al (), after briefly observing the targets in trivial scenarios, perceivers could achieve significant agreement on the evaluation of A, whereas in another study even in a carefully crafted trait‐relevant situation, perceivers failed to make an accurate judgement of A (McLarney‐Vesotski et al, ). Trait O is difficult to judge in some contexts (e.g.…”

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confidence: 99%

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Judging Personality from A Brief Sample of Behaviour: Detecting Where Others Stand on Trait Continua

Sheppard

Mitchell

2017

Eur J Pers

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Trait inferences occur routinely and rapidly during social interaction, sometimes based on scant or fleeting information. In this research, participants (perceivers) made inferences of targets' big‐five traits after briefly watching or listening to an unfamiliar target (a third party) performing various mundane activities (telling a scripted joke or answering questions about him/herself or reading aloud a paragraph of promotional material). Across three studies, when perceivers judged targets to be either low or high in one or more dimensions of the big‐five traits, they tended to be correct, but they did not tend to be correct when they judged targets as average. Such inferences seemed to vary in effectiveness across different trait dimensions and depending on whether the target's behaviour was presented either in a video with audio, a silent video, or just in an audio track—perceivers generally were less often correct when they judged targets as average in each of the big‐five traits across various information channels (videos with audio, silent videos, and audios). Study 3 replicated these findings in a different culture. We conclude with discussion of the scope and the adaptive value of this trait inferential ability. Copyright © 2017 European Association of Personality Psychology

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Personality perception: A developmental study

Cited by 19 publications

References 30 publications

Using Linguistic Cues for the Automatic Recognition of Personality in Conversation and Text

Using Linguistic Cues for the Automatic Recognition of Personality in Conversation and Text

Being Sherlock Holmes: Can we sense empathy from a brief sample of behaviour?

Judging Personality from A Brief Sample of Behaviour: Detecting Where Others Stand on Trait Continua

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