IJCAI 2021poster1 citations

SURPRISE! and When to Schedule It.

Zhihuan Huang, Shengwei Xu, You Shan, Yuxuan Lu, Yuqing Kong, Tracy Xiao Liu, Grant Schoenebeck

Abstract

Information flow measures, over the duration of a game, the audience’s belief of who will win, and thus can reflect the amount of surprise in a game. To quantify the relationship between information flow and audiences' perceived quality, we conduct a case study where subjects watch one of the world’s biggest esports events, LOL S10. In addition to eliciting information flow, we also ask subjects to report their rating for each game. We find that the amount of surprise in the end of the game plays a dominant role in predicting the rating. This suggests the importance of incorporating when the surprise occurs, in addition to the amount of surprise, in perceived quality models. For content providers, it implies that everything else being equal, it is better for twists to be more likely to happen toward the end of a show rather than uniformly throughout.

Agent-based and Multi-agent Systems: Algorithmic Game TheoryAgent-based and Multi-agent Systems: Computational Social ChoiceHumans and AI: Human Computation and Crowdsourcing
BibTeX
@inproceedings{ijcai2021p36,
  title     = {SURPRISE! and When to Schedule It.},
  author    = {Huang, Zhihuan and Xu, Shengwei and Shan, You and Lu, Yuxuan and Kong, Yuqing and Liu, Tracy Xiao and Schoenebeck, Grant},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on
               Artificial Intelligence, {IJCAI-21}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Zhi-Hua Zhou},
  pages     = {252--260},
  year      = {2021},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2021/36},
  url       = {https://doi.org/10.24963/ijcai.2021/36},
}
SURPRISE! and When to Schedule It. · IJCAI 2021