Attractive faces are rewarding irrespective of face category: Motivation in viewing attractive faces in Japanese viewers

Maiko Kobayashi, Katsumi Watanabe, Koyo Nakamura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Attractive faces have reward value for beholders, and thus people are motivated to view them. The incentive salience of attractive faces has been measured by using a pay-per-view key-pressing paradigm, wherein participants change the viewing time of a presented face image. For example, it was reported that male and female viewers were motivated to view attractive opposite-sex faces and cute infant faces longer than less attractive/cute faces. However, sex differences in the motivation to view attractive adult and cute infant faces were equivocal. We replicated previous observations from Caucasian populations that attractive faces are viewed longer than less attractive faces in a pay-per-view task in East-Asian populations. Results revealed that our male and female Japanese participants both made efforts to view attractive/cute faces irrespective of face category.

Original languageEnglish
Title of host publicationKST 2020 - 2020 12th International Conference on Knowledge and Smart Technology
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages186-190
Number of pages5
ISBN (Electronic)9781728144665
DOIs
Publication statusPublished - 2020 Jan
Event12th International Conference on Knowledge and Smart Technology, KST 2020 - Pattaya, Chonburi, Thailand
Duration: 2020 Jan 292020 Feb 1

Publication series

NameKST 2020 - 2020 12th International Conference on Knowledge and Smart Technology

Conference

Conference12th International Conference on Knowledge and Smart Technology, KST 2020
Country/TerritoryThailand
CityPattaya, Chonburi
Period20/1/2920/2/1

Keywords

  • Facial attractiveness
  • Facial cuteness
  • Motivation
  • Sex difference

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Decision Sciences (miscellaneous)
  • Information Systems and Management

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