A Network Model of Interpersonal Alignment in Dialog

Alexander Mehler, Andy Lücking, Petra Weiß
2010 Entropy  
In dyadic communication, both interlocutors adapt to each other linguistically, that is, they align interpersonally. In this article, we develop a framework for modeling interpersonal alignment in terms of the structural similarity of the interlocutors' dialog lexica. This is done by means of so-called two-layer time-aligned network series, that is, a time-adjusted graph model. The graph model is partitioned into two layers, so that the interlocutors' lexica are captured as subgraphs of an
more » ... passing dialog graph. Each constituent network of the series is updated utterance-wise. Thus, both the inherent bipartition of dyadic conversations and their gradual development are modeled. The notion of alignment is then operationalized within a quantitative model of structure formation based on the mutual information of the subgraphs that represent the interlocutor's dialog lexica. By adapting and further developing several models of complex network theory, we show that dialog lexica evolve as a novel class of graphs that have not been considered before in the area of complex (linguistic) networks. Additionally, we show that our framework allows for classifying dialogs according to their alignment status. To the best of our knowledge, this is the first approach to measuring alignment in communication that explores the similarities of graph-like cognitive representations. Keywords: alignment in communication; structural coupling; linguistic networks; graph distance measures; mutual information of graphs; quantitative network analysis [2], or (structurally) coupled, to borrow a term from system theory [3] . In what follows, we briefly introduce the core statements of the IAM. We start with its significance for theory construction in research on human communication. Thereupon, priming is described as the basic mechanism of alignment according to the IAM. In this context, the notion of paired primes is introduced, which plays a decisive role in this article. Finally, we explicate the widely excepted explanation that alignment is a matter of degree of the similarity of mental representations. This is a main proposition of the IAM and the starting point of the modeling and measuring framework of two-layer time-aligned network series introduced in this article. In the production as well as the comprehension of speech, interlocutors make use of mental representations of, so to speak, the meanings conveyed and the word forms encoding those meanings. These linguistic representations are, according to standard theories of speech processing following the hierarchical model of [4] , organized into levels, reflecting the linguistic layers involved "from intention to articulation". Accordingly, in dialog, alignment is found to take place in representations on all linguistic levels as, for example, the phonetic/phonological [5], the lexical [6], the syntactic [7], the semantic [8] level and on the level of situation models [9] . Since the linguistic levels are interconnected, alignment is, according to the IAM, supposed to percolate through these levels. Via this spreading of alignment, global alignment, that is, alignment of situation models-which are part and parcel of understanding-can be a result of local alignment on lower levels. In sum, the conception of alignment according to the IAM provides an account to the ease and efficiency of dialogical communication and therefore is a pivotal aspect of human communication.
doi:10.3390/e12061440 fatcat:maz7k53wtrhadn64ta7dssp4lu