A framework for the multimodal joint work of turn construction in face-to-face interaction

Gesture increases the face-to-face communication efficacy.Face-to-face efficacy is due to parallel feedback processing from all participants.The framework explains micro-level face-to-face interaction through dataflow.The framework can be used to understand face-to-face communication loop. We propose a framework for understanding the multimodal joint work of turn construction in face-to-face interaction. Using concepts from conversation analysis, nonverbal communication, and gesture studies, in a qualitative analysis of face-to-face interaction, we observe that, collaboratively and in a joint work, participants produce moves, within the current-speaker's turn, that allow them to deal with possible moves that could compromise the projectable trajectory of the interaction in progress. Working at the micro level of interaction, we propose a framework that will allows a better understanding of how a turn can be collaboratively produced and how other levels of sequence organization can be produced in order to achieve the desired social-agreement outcome.