International Symposium on Affective Science and Engineering
Online ISSN : 2433-5428
ISASE2025
Session ID : 3F02-03
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Affective Measurement 2
Analysis of asymmetry in the formation and change of good and bad evaluations on the avatar's personality
Taiki ETOTakashi SAKAMOTOToshikazu KATO
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CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract

This study explores the asymmetry in forming and changing evaluations of good and bad behaviors and compares these to evaluations of neutral probabilistic events. Moral judgments, particularly those shaped by negativity bias, show that negative impressions outweigh positive ones in their influence. Experiments involved participants watching video sequences of helping (good) or obstructing (bad) actions, followed by a questionnaire assessing the characters’ perceived morality. A second experiment assessed subjective probability judgments using a simulated coin-toss task. The findings reveal that a single bad action significantly disrupts perceptions of goodness built through repeated good actions, while a single good action does not sufficiently restore disrupted positive evaluations. Bad evaluations, however, show more resistance to change when formed through repeated bad actions, though they can be weakened by a subsequent good action. Comparisons with probability judgments highlight distinct cognitive processes, showing that evaluations of goodness are fragile and prone to negativity bias, whereas evaluations of badness are more persistent and robust. These results underscore the asymmetry in moral evaluations and its implications for understanding cognitive biases. The study has practical applications, such as identifying unconscious biases in communication or media, which could aid in creating tools to visualize and address these biases. By shedding light on the mechanisms of evaluation formation and transformation, the research offers insights that could contribute to the development of fairer societal systems and decision-making frameworks. Future work aims to deepen this understanding and mitigate bias at both individual and systemic levels.

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© 2025 Japan Society of Kansei Engineering
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