TY  - JOUR
AB  - 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 encompassing 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.
DA  - 2010
DO  - 10.3390/e12061440
KW  - network analysis
KW  - quantitative
KW  - mutual information of graphs
KW  - graph distance measures
KW  - linguistic networks
KW  - structural coupling
KW  - alignment in communication
LA  - eng
IS  - 6
M2  - 1440
PY  - 2010
SN  - 1099-4300
SP  - 1440-1483
T2  - Entropy
TI  - A network model of interpersonal alignment in dialog
UR  - https://nbn-resolving.org/urn:nbn:de:0070-pub-19487698
Y2  - 2024-11-22T01:31:09
ER  -