Pathfinder associative networks: studies in knowledge organization
Pathfinder associative networks: studies in knowledge organization
Dialogue act modeling for automatic tagging and recognition of conversational speech
Computational Linguistics
Latent semantic analysis for dialogue act classification
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
Feedback for guiding reflection on teamwork practices
Proceedings of the 2007 international ACM conference on Supporting group work
Visualizing real-time language-based feedback on teamwork behavior in computer-mediated groups
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Comparability of LSI and human judgment in text analysis tasks
MMACTEE'09 Proceedings of the 11th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering
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We describe two approaches to analyzing and tagging team discourse using Latent Semantic Analysis (LSA) to predict team performance. The first approach automatically categorizes the contents of each statement made by each of the three team members using an established set of tags. Performance predicting the tags automatically was 15% below human agreement. These tagged statements are then used to predict team performance. The second approach measures the semantic content of the dialogue of the team as a whole and accurately predicts the team's performance on a simulated military mission.