Conversation Analysis of Coalition Communication in Network Centric Operations

Introduction

Current major military deployment almost always involves collaborations among multiple nations with groups and team members from diverse backgrounds (Pierce 2002a, 2002b; Chiarelli and Michaelis 2005). The success of coalition operations requires highly effective and efficient communication between teams and team members. In a network centric environment in this Information Age, human communication constitutes an important dimension of the human networks, interacting with other types of networks such as communication networks and information networks. The degree of effectiveness of human communication will impact on the degree of the coalition interoperability, determining the effectiveness of coalition forces. However, it has been recognized that diverse backgrounds among multinational groups and team members have presented serious challenges in coalition communication (Pierce 2002a, 2002b; Chiarelli and Michaelis 2005). The challenges include frequent miscommunication among coalition teams. The related issues have been studied from various perspectives and methods including automated methods and techniques. In recent years, statistical or numerical text analysis methods such as Latent Semantic Analysis (henceforth LSA, Landauer et al. 1998) have been used to automate analysis and measurement of team communication conversation and discourse. In this chapter, we examine this human dimension of the coalition network in a network-centric context. In particular, we investigate the nature of miscommunication in coalition operations by exploring computational approaches to conversation analysis. Language is used in complex ways involving linguistic, cognitive, cultural and contextual differences. We focus on linguistic variations and variations of language use in Command and Control (C2) and planning in military coalition teams, especially among teams and members from English-speaking countries. We conduct an exploratory analysis of the discourse data resulting from a mission execution simulation commonly known as the Singapore Data.¹ We also report our analysis of data collected from interviews of UK and US military officers who had experienced miscommunications with coalition partners during multination training and operations.

Our analyses suggest that many relevant issues are largely pragmatic in nature, beyond not only lexical and grammatical differences but also “semantic” (topic) similarity of the communication content. This supports our on-going efforts to develop a computational pragmatics methodology. Departing from conventional computational approaches to language, this approach aims to understand the use of language in a social and communicative context by incorporating social, discourse and contextual information following the tradition advanced by Austin (1962) and Grice (1978, 1989), among other researchers. We believe that pragmatic dimensions such as speech acts (Austin 1962; Searle 1969) and conversation sequence patterns (Sacks 1992) are important parameters to successful understanding of the true nature of communication threads, especially the evaluation of communication effectiveness.