  Millions of people participate in online peer-to-peer support sessions, yet
there has been little prior research on systematic psychology-based evaluations
of fine-grained peer-counselor behavior in relation to client satisfaction.
This paper seeks to bridge this gap by mapping peer-counselor chat-messages to
motivational interviewing (MI) techniques. We annotate 14,797 utterances from
734 chat conversations using 17 MI techniques and introduce four new
interviewing codes such as chit-chat and inappropriate to account for the
unique conversational patterns observed on online platforms. We automate the
process of labeling peer-counselor responses to MI techniques by fine-tuning
large domain-specific language models and then use these automated measures to
investigate the behavior of the peer counselors via correlational studies.
Specifically, we study the impact of MI techniques on the conversation ratings
to investigate the techniques that predict clients' satisfaction with their
counseling sessions. When counselors use techniques such as reflection and
affirmation, clients are more satisfied. Examining volunteer counselors' change
in usage of techniques suggest that counselors learn to use more introduction
and open questions as they gain experience. This work provides a deeper
understanding of the use of motivational interviewing techniques on
peer-to-peer counselor platforms and sheds light on how to build better
training programs for volunteer counselors on online platforms.
