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Human communication is more than just the transmission of information. It also involves complex interaction dynamics that reflect the roles and communication styles of the participants. A novel approach to studying human communication is to view conversation as a coupled time series and apply analysis techniques from dynamical systems to the recurring topics or concepts. In this paper, we define a set of metrics that enable quantification of the complex interaction dynamics visible in conceptual recurrence. These multi-participant recurrence (MPR) metrics can be seen as an extension of recurrence quantification analysis (RQA) into the symbolic domain. This technique can be used to monitor the state of a communication system and inform about interaction dynamics, including the level of topic consistency between participants; the timing of state changes for the participants as a result of changes in topic focus; and, patterns of topic proposal, reflection, and repetition. We demonstrate three use studies applying the new metrics to conversation transcripts from different genres to demonstrate their ability to characterize individual communication participants and intergroup communication patterns.
Audio, Speech, and Language Processing, IEEE Transactions on (Volume:20 , Issue: 6 )
Date of Publication: Aug. 2012