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dc.contributor.authorArnade, Elizabeth Amaliaen_US
dc.date.accessioned2015-07-11T06:00:19Z
dc.date.available2015-07-11T06:00:19Z
dc.date.issued2014-01-15en_US
dc.identifier.othervt_gsexam:1898en_US
dc.identifier.urihttp://hdl.handle.net/10919/54538
dc.description.abstractEmotions are thought to play a crucial role in food behavior. Non-rational emotional decision making may be credited as the reason why consumers select what, how, and when they choose to interact with a food product. In this research, three experiments were completed for the overall goal of understanding the usefulness and validity of selected emotional measurement tools, specifically emotion questionnaire ballots and facial expression analysis, as compared to conventional sensory methods in developing a holistic view of product interest and engagement. Emotional response to 1% low-fat unflavored and chocolate-flavored milk was evaluated by using an emotion-based questionnaire as well as facial expression analysis software, to measure post-experience cognitive and in-the-moment intrinsic (implicit) emotional response, respectively. The software correlated facial movements of participants to associated basic emotions to estimate with what degree consumers were expressing these measured emotions upon presentation of each sample. Finally, the adapted facial expression method was compared to expected measurements from previous studies by measuring emotional facial response to four (sweet, salt, sour, and bitter) basic tastes. The cognitive emotion ballot and implicit facial analysis were able to differentiate between milk samples and offer a greater understanding of the consumer experience. Validity of the facial expression method was lacking for reasons including high individual taste variability, social context, intensities of stimuli, quality of video data capture, calibration settings, sample size number, analysis duration, and software sensitivity limitations. To better validate automatic facial expression methodology, further study is needed to investigate and minimize method limitations.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis Item is protected by copyright and/or related rights. Some uses of this Item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectbasic tasteen_US
dc.subjectemotionsen_US
dc.subjectmilken_US
dc.subjectfacial recognition softwareen_US
dc.subjectfacial expressionsen_US
dc.subjectfacial codingen_US
dc.titleMeasuring Consumer Emotional Response to Tastes and Foods through Facial Expression Analysisen_US
dc.typeThesisen_US
dc.contributor.departmentFood Science and Technologyen_US
dc.description.degreeMaster of Science in Life Sciencesen_US
thesis.degree.nameMaster of Science in Life Sciencesen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineFood Science and Technologyen_US
dc.contributor.committeechairDuncan, Susan E.en_US
dc.contributor.committeememberDunsmore, Julie C.en_US
dc.contributor.committeememberO'Keefe, Sean F.en_US


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