The Electronically Activated Recorder (EAR): A device for sampling naturalistic daily activities and conversations

Mehl, Matthias R.; Pennebaker, James W.; Crow, Daniel; Dabbs, James M.; Price, John Holland

doi:10.3758/bf03195410

Cited by 437 publications

(450 citation statements)

References 10 publications

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“…Because accurately assessing sexual behavior is notoriously difficult and may be particularly difficult in men who are married and have children (39,40), future studies will require creative and well-validated methods (e.g., ref. 41).…”

Section: Discussionmentioning

confidence: 99%

Testicular volume is inversely correlated with nurturing-related brain activity in human fathers

Mascaro

Hackett²,

Rilling

2013

Proc. Natl. Acad. Sci. U.S.A.

123

102

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Despite the well-documented benefits afforded the children of invested fathers in modern Western societies, some fathers choose not to invest in their children. Why do some men make this choice? Life History Theory offers an explanation for variation in parental investment by positing a trade-off between mating and parenting effort, which may explain some of the observed variance in human fathers' parenting behavior. We tested this hypothesis by measuring aspects of reproductive biology related to mating effort, as well as paternal nurturing behavior and the brain activity related to it. Both plasma testosterone levels and testes volume were independently inversely correlated with paternal caregiving. In response to viewing pictures of one's own child, activity in the ventral tegmental area-a key component of the mesolimbic dopamine reward and motivation system-predicted paternal caregiving and was negatively related to testes volume. Our results suggest that the biology of human males reflects a trade-off between mating effort and parenting effort, as indexed by testicular size and nurturing-related brain function, respectively. empathy | sperm competition

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Section: Discussionmentioning

confidence: 99%

Testicular volume is inversely correlated with nurturing-related brain activity in human fathers

Mascaro

Hackett²,

Rilling

2013

Proc. Natl. Acad. Sci. U.S.A.

123

102

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“…desperation and they don't don't see [...] Personality was assessed by asking each student to fill in the Big Five Inventory questionnaire (John et al, 1991), which asks participants to evaluate on a 5 point scale how well their personality matches a series of descriptions. The second source of data consists of conversation extracts recorded using an Electronically Activated Recorder (EAR) (Mehl, Pennebaker, Crow, Dabbs, & Price, 2001), collected by Mehl et al (2006). To preserve the participants' privacy, only random snippets of conversation were recorded.…”

Section: Sources Of Language and Personalitymentioning

confidence: 99%

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

Mairesse¹,

Walker²,

Mehl³

et al. 2007

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728

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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“…Alternatively, researchers can use smartphones to passively collect EMA data. For example, the Electronically Activated Recorder (EAR; Mehl, Pennebaker, Crow, Dabbs, & Price, 2001) provides an observer-based ecologically valid measure of daily behavior that can be used to estimate density distributions of (acoustically-detectable) personality states. However, before these methods can test fundamental questions about dynamic personality processes, we must first ask some basic questions about what we are measuring when we are assessing personality states.…”

Section: State Personalitymentioning

confidence: 99%

“…Future research should supplement EMA with other, non-self-report methods. Specifically, the Electronically Activated Recorder (EAR; Mehl et al, 2001) provides an observer-based measure of overt behavior (e.g., talkativeness, kindness) and some features of the situation (e.g., socializing vs. working, topic of conversation, etc.). Of course, the EAR has its own set of methodological limitations, but a combination of EMA and EAR methods would allow researchers to untangle which results are specific to the self's perspective and which are robust across methods.…”

Section: Strengths and Limitationsmentioning

confidence: 99%

Are fluctuations in personality states more than fluctuations in affect?

Wilson

Thompson

Vazire

2017

Journal of Research in Personality

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People fluctuate in their behavior as they go about their daily lives, but little is known about the processes underlying these fluctuations. In two ecological momentary assessment studies (Ns = 124, 415), we examined the extent to which negative and positive affect accounted for the within-person variance in Big Five states. Participants were prompted six times a day over six days (Study 1) or four times a day over two weeks (Study 2) to report their recent thoughts, feelings, and behaviors. Multilevel modeling results indicated that negative and positive affect account for most, but not all, of the within-person variance in personality states. Importantly, situation variables predicted variance in some personality states even after accounting for fluctuations in affect, indicating that fluctuations in personality states may be more than fluctuations in state affect.

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The Electronically Activated Recorder (EAR): A device for sampling naturalistic daily activities and conversations

Cited by 437 publications

References 10 publications

Testicular volume is inversely correlated with nurturing-related brain activity in human fathers

Testicular volume is inversely correlated with nurturing-related brain activity in human fathers

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

Are fluctuations in personality states more than fluctuations in affect?

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