@inproceedings{KornStammMoeckl2017, author = {Oliver Korn and Lukas Stamm and Gerd M{\"o}ckl}, title = {Designing Authentic Emotions for Non-Human Characters. A Study Evaluating Virtual Affective Behavior}, series = {DIS '17: Proceedings of the 2017 Conference on Designing Interactive Systems}, publisher = {ACM Press}, address = {New York}, organization = {Association for Computing Machinery}, isbn = {978-1-4503-4922-2}, doi = {10.1145/3064663.3064755}, pages = {477 -- 487}, year = {2017}, abstract = {While human emotions have been researched for decades, designing authentic emotional behavior for non-human characters has received less attention. However, virtual behavior not only affects game design, but also allows creating authentic avatars or robotic companions. After a discussion of methods to model and recognize emotions, we present three characters with a decreasing level of human features and describe how established design techniques can be adapted for such characters. In a study, 220 participants assess these characters' emotional behavior, focusing on the emotion \"anger\". We want to determine how reliable users can recognize emotional behavior, if characters increasingly do not look and behave like humans. A secondary aim is determining if gender has an impact on the competence in emotion recognition. The findings indicate that there is an area of insecure attribution of virtual affective behavior not distant but close to human behavior. We also found that at least for anger, men and women assess emotional behavior equally well.}, language = {en} }