Affective Forecasting and Memory Biases during the Tokyo and Beijing Olympics

Area of Science:

• Psychology
• Social Psychology
• Behavioral Economics

Background:

• Affective forecasting models predict future emotions based on outcome specifications.
• Previous research suggests over/underestimation of future emotions is common.
• The applicability of these models to real-world public events remains underexplored.

Purpose of the Study:

• To test the applicability of Buechel et al.'s (2017) affective forecasting framework to large-scale public events.
• To examine emotional prediction and recall during the Tokyo and Beijing Olympics amidst the COVID-19 pandemic.
• To investigate factors influencing emotional under/overestimation and memory biases.

Main Methods:

• Longitudinal online surveys administered to 2,059 (Tokyo) and 2,595 (Beijing) participants in Japan.
• Data collected before, during, and after the Olympic Games.
• Analysis of affective forecasting and emotional memory biases.

Main Results:

• Consistent with the framework, positive emotions during the Olympics were generally underestimated.
• Individuals opposing the events showed greater underestimation of positive emotions.
• Recollection of emotional experiences was influenced by contextual factors, including perceived infection rates.

Conclusions:

• The study validates the use of affective forecasting models in real-world, large-scale societal contexts.
• Emotional prediction and memory are susceptible to biases influenced by event characteristics and contextual factors.
• Findings enhance understanding of human emotional responses during major global events.