Fig. 1. A framework for studying conversation.

The results are organized according to an analytic framework that distinguishes between three related levels of conversation. Low-level features can be observed directly, vary over short time periods, and often relate to conversational structure (e.g., a pause at the end of a speaker’s turn). Mid-level features are generally inferred indirectly by human perceivers or algorithms that approximate human perception, vary on a medium-frequency or turn-by-turn basis, and capture linguistic or paralinguistic conversational content (e.g., a happy facial expression or vocal emotional intensity). High-level features relate to people’s subjective judgments of a conversation (e.g., postconversation-reported enjoyment or people’s evaluations of their partner). Subsequent sections present empirical results at each level of the hierarchy, as well as analyses that demonstrate the interplay across levels that we believe will represent an increasingly common and important type of research.