Competing With Artificial Intelligence Or Other Fans: Effects of Making Predictions About Game Outcome on Fans' Perceived Curiosity and Evaluations of Game Consumption.
Saved in:
| Title: | Competing With Artificial Intelligence Or Other Fans: Effects of Making Predictions About Game Outcome on Fans' Perceived Curiosity and Evaluations of Game Consumption. |
|---|---|
| Authors: | Jang, Wonseok (AUTHOR), Zhuo, Gong (AUTHOR), Pyun, Hyunwoong (AUTHOR), Lee, Gyemin (AUTHOR) |
| Source: | International Journal of Human-Computer Interaction. Jan2025, Vol. 41 Issue 1, p765-774. 10p. |
| Subjects: | Human-computer interaction, Sports spectators, Artificial intelligence, Curiosity, Forecasting |
| Abstract: | This study focused on whether predicting the game outcome prior to watching the actual game results in more positive evaluations of game consumption from sports fans through heightened perceived curiosity and flow. This study employed a 4 (prediction type: no prediction vs. simple prediction vs. prediction and compete against AI vs. prediction and compete against other fans) × 2 (game outcome: winning vs. losing) between-subjects design. The results suggest that fans who make predictions about the outcome before watching highlight videos experience greater feelings of curiosity and flow, and more positive evaluations of game consumptions in comparison to those who do not make any predictions prior to watching the game. Our findings not only contribute to fan behavior and human-computer interaction literature by examining the role of prediction and curiosity but also offer meaningful practical implications for developing effective fan engagement interfaces by incorporating the elements of prediction and competition. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
