  Linguistic coordination is a well-established phenomenon in spoken
conversations and often associated with positive social behaviors and outcomes.
While there have been many attempts to measure lexical coordination or
entrainment in literature, only a few have explored coordination in syntactic
or semantic space. In this work, we attempt to combine these different aspects
of coordination into a single measure by leveraging distances in a neural word
representation space. In particular, we adopt the recently proposed Word
Mover's Distance with word2vec embeddings and extend it to measure the
dissimilarity in language used in multiple consecutive speaker turns. To
validate our approach, we apply this measure for two case studies in the
clinical psychology domain. We find that our proposed measure is correlated
with the therapist's empathy towards their patient in Motivational Interviewing
and with affective behaviors in Couples Therapy. In both case studies, our
proposed metric exhibits higher correlation than previously proposed measures.
When applied to the couples with relationship improvement, we also notice a
significant decrease in the proposed measure over the course of therapy,
indicating higher linguistic coordination.
