  Dyadic interactions among humans are marked by speakers continuously
influencing and reacting to each other in terms of responses and behaviors,
among others. Understanding how interpersonal dynamics affect behavior is
important for successful treatment in psychotherapy domains. Traditional
schemes that automatically identify behavior for this purpose have often looked
at only the target speaker. In this work, we propose a Markov model of how a
target speaker's behavior is influenced by their own past behavior as well as
their perception of their partner's behavior, based on lexical features. Apart
from incorporating additional potentially useful information, our model can
also control the degree to which the partner affects the target speaker. We
evaluate our proposed model on the task of classifying Negative behavior in
Couples Therapy and show that it is more accurate than the single-speaker
model. Furthermore, we investigate the degree to which the optimal influence
relates to how well a couple does on the long-term, via relating to
relationship outcomes
