Emotion Measurement

Meiselman, Herbert L.

doi:10.1016/b978-0-08-100508-8.00026-6

Cited by 43 publications

(23 citation statements)

References 77 publications

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“…Moreover, it is evident that automated facial expression analysis (e.g., Noldus's FaceReader) can produce valid data for prototypical facial expressions that are recorded under standardized conditions (Lewinski et al, 2014;Littlewort et al, 2006;Valstar et al, 2011). The present findings support the skepticism that current automated facial expression analysis is not yet mature enough for operational use (Meiselman, 2016) by revealing that, while iMotions's automated facial expression analysis can produce data with an acceptable degree of accuracy for prototypical facial expressions, it is less accurate for subtle, more natural facial expressions.…”

Section: Validation and Comparison Of Imotions (Affdex And Facet)supporting

confidence: 69%

“…This movement typically occurs when expressing emotions such as anger, disgust, or sadness (Du, Tao, & Martinez, 2014;Ekman & Friesen, 2003). Given that there are numerous publications that address theoretical and practical aspects of FACS (e.g., Ekman & Friesen, 1976;Hwang & Matsumoto, 2016;Meiselman, 2016), we do not discuss these in more detail.…”

Section: The Origins Of Facial Expression Analysismentioning

confidence: 99%

“…This research contributes by independently measuring and comparing the performance of iMotions's AFFDEX and FACET modules, and making the results publicly available for a broad audience. In general, there is support for the idea that automated facial expression analysis is technically feasible (e.g., Baltrusaitis et al, 2016;Bartlett, Hager, Ekman, & Sejnowski, 1999;Lien, Kanade, Cohn, & Li, 1998;Littlewort, Bartlett, Fasel, Susskind, & Movellan, 2006;Meiselman, 2016;Vallverdu, 2014). Moreover, it is evident that automated facial expression analysis (e.g., Noldus's FaceReader) can produce valid data for prototypical facial expressions that are recorded under standardized conditions (Lewinski et al, 2014;Littlewort et al, 2006;Valstar et al, 2011).…”

Section: Validation and Comparison Of Imotions (Affdex And Facet)mentioning

confidence: 99%

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Facial expression analysis with AFFDEX and FACET: A validation study

et al. 2017

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The goal of this study was to validate AFFDEX and FACET, two algorithms classifying emotions from facial expressions, in iMotions's software suite. In Study 1, pictures of standardized emotional facial expressions from three databases, the Warsaw Set of Emotional Facial Expression Pictures (WSEFEP), the Amsterdam Dynamic Facial Expression Set (ADFES), and the Radboud Faces Database (RaFD), were classified with both modules. Accuracy (Matching Scores) was computed to assess and compare the classification quality. Results show a large variance in accuracy across emotions and databases, with a performance advantage for FACET over AFFDEX. In Study 2, 110 participants' facial expressions were measured while being exposed to emotionally evocative pictures from the International Affective Picture System (IAPS), the Geneva Affective Picture Database (GAPED) and the Radboud Faces Database (RaFD). Accuracy again differed for distinct emotions, and FACET performed better. Overall, iMotions can achieve acceptable accuracy for standardized pictures of prototypical (vs. natural) facial expressions, but performs worse for more natural facial expressions. We discuss potential sources for limited validity and suggest research directions in the broader context of emotion research.

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Section: Validation and Comparison Of Imotions (Affdex And Facet)supporting

confidence: 69%

Section: The Origins Of Facial Expression Analysismentioning

confidence: 99%

Section: Validation and Comparison Of Imotions (Affdex And Facet)mentioning

confidence: 99%

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Facial expression analysis with AFFDEX and FACET: A validation study

et al. 2017

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“…El tema de las emociones ha tomado relevancia en el diseño; una muestra de ello es la publicación reciente del libro Emotion Measurment que discute cómo medir las emociones de objetos tales como marcas, productos o servicios (Meiselman, 2016). El tema, además, interesa tanto a la academia como a la industria (Mahut, Bouchard, Omhover, Favart, & Esquivel, 2018).…”

Section: Juan Carlos Ortiz Nicolás Irma Hernández Lópezunclassified

Emociones específicas en la interacción persona-producto: un método de identificación causal

Nicolás

López²

2018

Econ. Creativa

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Esta investigación presenta y valida un método cualitativo para identificar las causas que estimulan emociones particulares en la interacción persona-producto. El desarrollo y la validación del método incluyó un estudio divido en cuatro etapas: 1) Diseño del método, 2) Construcción, 3) Implementación y 4) Validación. El método propuesto considera cinco fases: A. Selección del producto a evaluar, B. Determinación de características de participantes y lugar de evaluación, C. Identificación de las emociones, D. Codificación y análisis, y E. Reporte de resultados. Para implementar el método se evaluaron dos estímulos (alcancía y silla). En la validación se utilizan los mismos estímulos y un método cuantitativo. Este diseño experimental fue establecido para comparar los datos obtenidos. Los resultados indican que el método propuesto es efectivo para identificar las causas que estimularon la reacción emocional en la interacción persona-producto. Identificar las causas que estimulan una emoción es esencial para practicar diseño emocional.

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“…More precisely, we hypothesized that contextual information of luxury would elicit the concept related to luxury (e.g., prestige and quality) and influence the emotional response. Since an emotional response is understood to consist of changes in several components, not only should we be able to retrieve changes via questionnaires (measuring feelings), but other indicators of emotional components should also emerge through physiological responses and facial motor expressions (for an overview, see Meiselman, 2016). We conducted an experiment in which participants had to smell perfumes and assess them while physiological and expressive measures were recorded.…”

Section: Introductionmentioning

confidence: 99%

“Dior, J’adore”: The role of contextual information of luxury on emotional responses to perfumes

Baer

Coppin

Porcherot

et al. 2018

Food Quality and Preference

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Luxury conveys values of quality and rarity and holds a particular emotional meaning. Yet, studies conducted on the impact of contextual information of luxury on emotional responses to products remain scarce. In this study, we tested whether contextual information, in particular evoking luxury, could influence emotional responses to perfumes, which are known to be powerful elicitors of emotion. More specifically, we measured the subjective, physiological, and expressive components of participants' emotional responses. We conducted an experiment in which participants had to smell and assess perfumed pens as well as blank pens (i.e., without perfume) presented either in a luxurious context (i.e., name, brand and bottle), a non-luxurious one, or no information. Results indicated that participants tended to rate perfumes as more pleasant and rated them as more familiar when presented in a luxurious context than in a non-luxurious one or without context, and the blank pen as more irritating in a non-luxurious context than in a luxurious one. However, we did not find evidence of a significant contextual information effect on expressive or physiological indicators. Our findings suggest that contextual information of luxury can moderately influence the subjective component of participants' emotional responses, while no evidence for such effect was found with respect to the physiological and expressive components.

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Emotion Measurement

Cited by 43 publications

References 77 publications

Facial expression analysis with AFFDEX and FACET: A validation study

Facial expression analysis with AFFDEX and FACET: A validation study

Emociones específicas en la interacción persona-producto: un método de identificación causal

“Dior, J’adore”: The role of contextual information of luxury on emotional responses to perfumes

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