Using Speech Act Theory to Apply Automated Communications Analysis to Distributed Sensemaking

Abstract

In this paper, computational linguistics is applied to define and capture Speech Acts in distributed sensemaking in a military map-exercise. The exercise was performed by teams of three participants playing the role of Company Commanders (assisted by a team of confederates) using either text-only or a combination of voice and text communications, using either basic or elaborated reporting formats. Analysis of communications was performed in terms of network structure (i.e., who spoke with whom), topics (derived, using Latent Dirichlet Allocation, from all communications and from the speech of the Commanders), and speech acts reveals differences between conditions. It is proposed that the ‘topics’ uncovered through the analysis is analogous with the ‘frame’ in Data-Frame Model of sensemaking. In this way, it is possible to identify how frames are introduced, questioned and elaborated during communications in a team-based Command and Control exercise. Further, analyzing speech acts for different topics and under different conditions showed how different communication media or report formats can help or hinder team activity. It is proposed that such analysis could be viable for monitoring and supporting team communications, particularly during training exercises, but potentially as a route to providing automated decision and sensemaking support to teams.