Best Paper Award for the 11th International Conference on Social Computing and Social Media, in the context of HCI International 2019, 16-31 July 2019, Orlando, FL, USA
Certificate for Best Paper Award of the 11th International Conference on Social Computing and Social Media
Candy Olivia Mawalim (Japan Advanced Institute of Science and Technology, Japan),
Shogo Okada (Japan Advanced Institute of Science and Technology / RIKEN AIP, Japan),
Yukiko I. Nakano (Seikei University / RIKEN AIP, Japan)
and Masashi Unoki (Japan Advanced Institute of Science and Technology, Japan)
for the paper entitled
"Multimodal BigFive Personality Trait Analysis using Communication Skill Indices and Multiple Discussion Types Dataset"
Presented in the context of
HCI International 2019
16-31 July 2019, Orlando, FL, USA
"This paper focuses on multimodal analysis in multiple discussion types dataset for estimating BigFive personality traits. The analysis was conducted to achieve two goals: First, clarifying the effectiveness of multimodal features and communication skill indices to predict the BigFive personality traits. Second, identifying the relationship among multimodal features, discussion type, and the BigFive personality traits. The MATRICS corpus, which contains of three discussion task types dataset, was utilized in this experiment. From this corpus, three sets of multimodal features (acoustic, head motion, and linguistic) and communication skill indices were extracted as the input for our binary classification system. The evaluation was conducted by using F1-score in 10-fold cross validation. The experimental results showed that the communication skill indices are important in estimating agreeableness trait. In addition, the scope and freedom of conversation affected the performance of personality traits estimator. The freer a discussion is, the better personality traits estimator can be obtained."
The full paper is available through SpringerLink, provided that you have proper access rights.