Demo Data from SIGIR 2026 / reviewers in the wild / expert
June Kang
dblp:182/7357
· DBLP profile ↗
3ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0003-3625-0856ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2Human-computer interaction and ubiquitous computing · 2 · 1 first-author · 1 since 2021Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Virtual and augmented reality · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Immersive interaction · 44% Usability and user experience research · 44% Games and playful interaction · 13% |
Topics — the 3 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality › virtual environment
driving simulation |
0.4 | 1 | 2019 | You or Me? Personality Traits Predict Sacrificial Decisions in an Accident Situation · IEEE Trans. Vis. Comput. Graph. 2019 |
Immersive interaction › virtual reality
driving simulation |
0.2 | 1 | 2016 | Personality differences predict decision-making in an accident situation in virtual driving · VR 2016 |
Games and playful interaction
serious games |
0.1 | 1 | 2016 | Personality differences predict decision-making in an accident situation in virtual driving · VR 2016 |
Methods — techniques the papers use, named apart from their topics
virtual reality simulation · 0.4personality trait analysis · 0.4user study · 0.2personality questionnaires · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | A preliminary study on Reading the Mind in the Eyes of the Robot *abstractAs social robots are increasingly deployed, the interaction between human and robot is becoming more important. Affective theory of mind (ToM) is one of the core components of emotional communication between human, enabling recognize and understand other’s emotional state as an independent agent separate from oneself. Current study developed robot version of widely adopted test of affective ToM, Reading the Mind in the Eyes Test (RMET) using a social robot, Vector. In the preliminary study, we compared the participants performance in both robot version, ingroup (East Asian) and outgroup (Caucasian) human version of RMET, the individual variance of affective ToM toward human expression is reproduced to the expressions of the Vector robot. Moreover, only the performance toward the expressions of same ethnicity (RMET-K) predicts the performance on the robot expression (RMET-R). The result suggests that not only the quality of robot’s expression but the variance of social cognition level of the human should be considered in social robot development. June Kang, Yeo Eun Park |
RO-MAN | 1 |
| 2019 | You or Me? Personality Traits Predict Sacrificial Decisions in an Accident SituationabstractEmergency situations during car driving sometimes force the driver to make a sudden decision. Predicting these decisions will have important applications in updating risk analyses in insurance applications, but also can give insights for drafting autonomous vehicle guidelines. Studying such behavior in experimental settings, however, is limited by ethical issues as it would endanger peoples' lives. Here, we employed the potential of virtual reality (VR) to investigate decision-making in an extreme situation in which participants would have to sacrifice others in order to save themselves. In a VR driving simulation, participants first trained to complete a difficult course with multiple crossroads in which the wrong turn would lead the car to fall down a cliff. In the testing phase, obstacles suddenly appeared on the "safe" turn of a crossroad: for the control group, obstacles consisted of trees, whereas for the experimental group, they were pedestrians. In both groups, drivers had to decide between falling down the cliff or colliding with the obstacles. Results showed that differences in personality traits were able to predict this decision: in the experimental group, drivers who collided with the pedestrians had significantly higher psychopathy and impulsivity traits, whereas impulsivity alone was to some degree predictive in the control group. Other factors like heart rate differences, gender, video game expertise, and driving experience were not predictive of the emergency decision in either group. Our results show that self-interest related personality traits affect decision-making when choosing between preservation of self or others in extreme situations and showcase the potential of virtual reality in studying and modeling human decision-making. Ui Jong Ju, June Kang, Christian Wallraven |
IEEE Trans. Vis. Comput. Graph. | 2 |
| 2016 | Personality differences predict decision-making in an accident situation in virtual drivingabstractUnderstanding how humans make decisions in challenging situations - such as trying to save peoples' lives even though this endangers one's own life - is crucial in optimizing rescue operations and dealing with natural disasters and other crises. The experimental study of these decisions, however, has often been done using text-based surveys, which is known to emphasize rational and reflective judgments. Here, we used virtual reality to investigate decision-making in a real-world context, in which a decision needs to be made intuitively under time pressure - for this we simulated an accident situation in an immersive virtual driving scenario. In the scenario, participants were told to race a course as fast as possible. After training, participants were confronted with the sudden appearance of pedestrians on the race course. We observed three different behaviors: group one ignored the pedestrians and/or hit the accelerator, group two hit the brake, and group three tried to steer the car to avoid pedestrians. We found that most Avoid-group participants had more real and virtual driving experience compared to the other two groups and they also felt more competent during the game as measured by subjective game experience questionnaires. Importantly, results from established personality questionnaires showed that participants who did not brake (therefore potentially harming the pedestrians) had significantly lower scores in perspective-taking and higher scores in psychopathy compared to participants who tried to avoid the accident situation. Our results demonstrate that personality differences to some degree are able to predict intuitive decision-making and that such processes can be studied in a controlled, immersive VR simulation. Ui Jong Ju, June Kang, Christian Wallraven |
VR | 2 |