social computing; nonverbal behavior; multimodal modeling; social interaction modeling; social media
Avci Umut and Aran Oya (2016), Predicting the Performance in Decision-Making Tasks: From Individual Cues to Group Interaction, in IEEE Transactions on Multimedia
, 18(4), 643-658.
Okada Shogo, Aran Oya, Gatica-Perez Daniel (2015), Personality Trait Classification via Co-Occurrent Multiparty Multimodal Event Discovery, in Proceedings of the 2015 ACM on International Conference on Multimodal Interaction
, Seattle, WA, USAACM, New York, NY, USA.
Aran Oya, Biel Joan-Isaac, Gatica-Perez Daniel (2014), Broadcasting oneself: Visual Discovery of Vlogging Styles, in IEEE Transactions on Multimedia
, 16(1), 201-215.
Avci Umut, Aran Oya (2014), Effect of nonverbal behavioral patterns on the performance of small groups, in Proceedings of the 2014 Workshop on Understanding and Modeling Multiparty, Multimodal Interactions
, ACM Newyork, USA.
Cerekovic Aleksandra, Aran Oya, Gatica-Perez Daniel (2014), How Do You Like Your Virtual Agent?: Human-Agent Interaction Experience through Nonverbal Features and Personality Traits, in Human Behavior Understanding
, Springer, US.
Salah Albert Ali, Hung Hayley, Aran Oya, Gunes Hatice (2013), Creative Applications of Human Behavior Understanding, in Human Behavior Understanding, Lecture Notes in Computer Science
, 8212, 1-14.
Aran Oya, Gatica-Perez Daniel (2013), Cross-domain personality prediction: from video blogs to small group meetings, in International conference on multimodal interaction, ICMI 2013
, Sydney, AustraliaACM, Newyork, USA.
Salah Albert Ali (ed.) (2013), Human Behavior Understanding - 4th International Workshop, HBU 2013, Barcelona, Spain, October 22, 2013. Lecture Notes in Computer Science 8212
, Springer, Switzerland.
Aran Oya, Gatica-Perez Daniel (2013), One of a kind: inferring personality impressions in meetings, in International Conference on Multimodal Interaction, ICMI 2013
, Sydney, AustraliaACM, Newyork USA.
Kindiroǧlu Ahmet Alp, Akarun Lale, Aran Oya (2013), Vision based personality analysis using transfer learning methods, in Signal Processing and Communications Applications Conference (SIU), 2014 22nd
, Trabzon, TurkeyIEEE, USA.
Sanchez-Cortes Dairazalia, Aran Oya, Jayagopi Dinesh Babu, Schmid Mast Marianne, Gatica-Perez Daniel (2012), Emergent leaders through looking and speaking: from audio-visual data to multimodal recognition, in Journal on Multimodal User Interfaces
Kalimeri Kyriaki, Lepri Bruno, Aran Oya, Jayagopi Dinesh Babu, Gatica-Perez Daniel, Pianesi Fabio (2012), Modeling dominance effects on nonverbal behaviors using granger causality, in Proceedings of International Conference on Multimodal Interaction, ICMI 2012
, Santa Monica, CAACM, Newyork, USA.
Aran Oya, Ari Ismail, Kindiroglu Alp, Santemiz Pinar, Akarun Lale, Automatic Sign Language Recognition and Applications for Turkish Sign Language (in Turkish), in Arik Engin (ed.), Koc University Press, Turkey.
Kara Yunus Emre, Genc Gaye, Aran Oya, Akarun Lale, Modeling Annotator Behaviors for Crowd Labeling, in Neurocomputing
Cerekovic Aleksandra and Aran Oya and Gatica-Perez Daniel, Rapport with Virtual Agents: What do Human Social Cues and Personality Explain?, 2016, in IEEE Transactions on Affective Computing
Gatica-Perez Daniel, Aran Oya, Jayagopi Dinesh, Small Group Analysis, in Burgoon J. (ed.), Cambridge University Press, UK.
In the last decade, there is a strong interest on analyzing human actions, especially in smart room applications. However, the intelligence of these systems is limited to performing given tasks, without considering the social situation in the environment or the social behavior of the people in the surrounding. Among the range of applications that provide support systems in rooms equipped with sensing devices, the computational analysis of social interaction is an emerging field of research with the aims of converting these support systems to be socially aware. The research on computational social behavior analysis and this proposed research program in particular, aims to deliver research results that would enable the development of tools to improve quality of life, by collective decision making support systems, meeting support systems and systems for self-assessment, training, and education.This project proposes to build computational models of social constructs that define the social behavior of individuals and groups in face to face conversations, perceived via audio, visual or mobile sensors. The aim is to automatically analyze the social behavior of individuals during their interaction through their nonverbal signals and build models to estimate several social concepts using machine learning techniques. The novelty of the proposed approach is that it investigates computational approaches that make use of the close relation between related social constructs, such as dominance and leadership, or personality and dominance, during the learning process. The assumption is that these social constructs are related, thus automatic inference for one concept can take advantage of the other. The project follows a joint learning approach that combines the individual characteristics of participants in a group, such as personality and mood, with their social position in the group, such as dominance or roles, resulting from intra-group interaction and relations, as well as the overall group structure. Another novelty of the proposal is related to the usage of social media content to learn social behavior of individuals. Unlike the limited amount of data that is used to build computational models of social behavior, the social media sites provide an excellent and a vast amount of data for natural human behavior. The project aims to transfer the knowledge that can be extracted from the audio-visual behavioral content in social media (i.e. video blogging sites, video discussion sites, video lectures sites, etc.) to small group settings.My research program is structured in four main phases. The first phase consists of modeling individual characteristics of participants. For this purpose, a database collected from social media will be used together with annotations on personality and mood. Techniques to transfer the knowledge gained through this database to normal small group settings will be investigated in the second phase. The third phase of the project focuses on modeling the group interaction and group structure, and the fourth phase aims at developing a joint learning approach to learn related social tasks.