Using Knowledge Graph Dynamics to Describe Group Ideation Effectiveness in Problem Solving

Groups engaged in brainstorming undergo several types of ideation processes, some more effective than others. Current methods for characterizing the knowledge expressed in a group and its dynamics include embedding models and cosine distance between idea embeddings that do not find explicit semantic connections, or knowledge graphs that represent semantic connections but need large amounts of data to extract. We are proposing a novel idea graph model that combines embedding models and a graph representation of knowledge, together with a novel group problem-solving model. Using the graph representation and the evaluation measures, we identified and characterized more effective groups from experimental data and verified the main hypotheses derived from the theoretical model.