Group conversation is a frequently used form of communication for exchanging ideas and making decisions. Cohesion is an emergent phenomenon that describes the members' attraction towards the group and towards working together. In this paper, we present the cohesion labels assigned to segments from [redacted], a multimodal dataset of simulated medical consultations. Then, we present the analysis performed to identify social cues that characterize cohesion and report the accuracy for classifying cohesion. Results show that non-verbal social cues like gaze, facial AUs, laughter etc., indeed convey information regarding the level of cohesion. Finally we present a preliminary evaluation conducted using the prominent cues to simulate a cohesive group of agents.