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1. LuckyFind: Leveraging Surprise to Improve User Satisfaction and Inspire Curiosity in a Recommender System

   https://doi.org/10.1145/3406522.3446017  

   Niu, Xi; Al-Doulat, Ahmad (March 2021, CHIIR '21: Proceedings of the 2021 ACM SIGIR Conference on Human Information Interaction and Retrieval)

   null (Ed.)

   The growing amount of online information today has increased opportunity to discover interesting and useful information. Various recommender systems have been designed to help people discover such information. No matter how accurately the recommender algorithms perform, users’ engagement with recommended results has been complained being less than ideal. In this study, we touched on two human-centered objectives for recommender systems: user satisfaction and curiosity, both of which are believed to play roles in maintaining user engagement and sustain such engagement in the long run. Specifically, we leveraged the concept of surprise and used an existing computational model of surprise to identify relevantly surprising health articles aiming at improving user satisfaction and inspiring their curiosity. We designed a user study to first test the validity of the surprise model in a health news recommender system, called LuckyFind. Then user satisfaction and curiosity were evaluated. We find that the computational surprise model helped identify surprising recommendations at little cost of user satisfaction. Users gave higher ratings on interestingness than usefulness for those surprising recommendations. Curiosity was inspired more for those individuals who have a larger capacity to experience curiosity. Over half of the users have changed their preferences after using LuckyFind, either discovering new areas, reinforcing their existing interests, or stopping following those they did not want anymore. The insights of the research will make researchers and practitioners rethink the objectives of today’s recommender systems as being more human-centered beyond algorithmic accuracy. 

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2. SURPRISE! and When to Schedule It.

   https://doi.org/10.24963/ijcai.2021/36  

   Huang, Zhihuan; Xu, Shengwei; Shan, You; Lu, Yuxuan; Kong, Yuqing; Liu, Tracy Xiao; Schoenebeck, Grant (August 2021, Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence)

   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. 

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3. Surprise as an Emotion: A Response to Ortony

   https://doi.org/10.1177/17456916221132789  

   Neta, Maital; Kim, M_Justin (November 2022, Perspectives on Psychological Science)

   We write in response to an article published in this journal by Andrew Ortony titled “Are All ‘Basic Emotions’ Emotions? A Problem for the (Basic) Emotions Construct.” The author claimed that “for all its elevated status as a basic emotion, surprise fails to satisfy the minimal requirements that [he] proposed for something to be an emotion, and if it is not an emotion, it cannot possibly be a basic emotion.” Although we acknowledge the concerns brought forth by Ortony, we respectfully disagree with his conclusion about surprise. To make a case against the assertion that surprise is valence-free, we summarize an extensive body of work showing that surprise is indeed valenced—in a specific manner (i.e., ambiguously valenced)—and that it meets all of Ortony’s criteria for an emotion. In other words, rather than being described as neither positive nor negative, this emotion is either positive or negative. We consider the data with respect to surprise as a basic emotion, and we dispute the definitions of basic emotions as “widely divergent.” Future work is needed to continue defining an emotion, and a basic emotion, but we believe this is a worthy effort toward shaping a still evolving field. 

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4. When Success Is Surprising: Children’s Ability to Use Surprise to Infer Competence

   https://doi.org/10.1162/opmi.a.2  

   Asaba, Mika; Wu, Yang; Carrillo, Brandon; Gweon, Hyowon (May 2025, Open mind)

   Abstract How do we learn who is good at what? Building on the idea that humans draw rich inferences from others’ emotional expressions, here we ask whether others’ surprised reactions to performance outcomes can elicit inferences about competence. Across three experiments, participants were asked to choose “who is better” in scenarios where two students performed identically on the same task but their teacher expressed surprise to only one of them. In Experiment 1 (n = 60, adults) and Experiment 2 (n = 90, 6- to 8-year-old children), participants’ responses were modulated by not only the students’ performance outcomes (success or failure) but also the teacher’s response to the outcomes (surprise or no surprise). Specifically, participants preferentially chose the student who did not elicit the teacher’s surprise as more competent when both students succeeded, but chose the student who elicited surprise when both failed. Experiment 3a (n = 150, 4- to 8-year-olds) replicated this pattern in 6- to 8-year-olds as a group—but not in 4- to 5-year-olds—with increasing robustness with age. Finally, this pattern was significantly reduced in Experiment 3b where the teacher’s surprise was directed at an irrelevant event rather than the student’s performance (n = 90, 6- to 8-year-olds). Taken together, these results suggest that even non-valenced emotional reactions to performance outcomes—being surprised at someone’s success or failure—can inform inferences about valenced qualities such as competence. More broadly, the current findings demonstrate that emotional expressions we observe in our daily lives can lead to nuanced yet consequential social judgments. 

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5. Surprise! Predicting Infant Visual Attention in a Socially Assistive Robot Contingent Learning Paradigm

   https://doi.org/10.1109/RO-MAN46459.2019.8956385  

   Klein, Lauren; Itti, Laurent; Smith, Beth A.; Rosales, Marcelo; Nikolaidis, Stefanos; Matarić; Maja J. (October 2019, Ro-Man 2019- International Conference on Robot and Human Interactive Communication)

   Early intervention to address developmental disability in infants has the potential to promote improved outcomes in neurodevelopmental structure and function [1]. Researchers are starting to explore Socially Assistive Robotics (SAR) as a tool for delivering early interventions that are synergistic with and enhance human-administered therapy. For SAR to be effective, the robot must be able to consistently attract the attention of the infant in order to engage the infant in a desired activity. This work presents the analysis of eye gaze tracking data from five 6-8 month old infants interacting with a Nao robot that kicked its leg as a contingent reward for infant leg movement. We evaluate a Bayesian model of lowlevel surprise on video data from the infants’ head-mounted camera and on the timing of robot behaviors as a predictor of infant visual attention. The results demonstrate that over 67% of infant gaze locations were in areas the model evaluated to be more surprising than average. We also present an initial exploration using surprise to predict the extent to which the robot attracts infant visual attention during specific intervals in the study. This work is the first to validate the surprise model on infants; our results indicate the potential for using surprise to inform robot behaviors that attract infant attention during SAR interactions. 

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