1. A computer-implemented predictive modeling method comprising: obtaining conversation metric data and conversation assessment data for respective conversations included in a plurality of conversations, wherein the metric data for a respective conversation include data indicative of one or more values of one or more metrics for evaluating conversation quality, wherein the one or more metric values are determined based, at least in part, on communications of two or more participants in the conversation, wherein the metrics include a proportionality metric and/or a matching metric, wherein a value of the proportionality metric depends on proportions of communication contributed to the conversation by the two or more participants, wherein a value of the matching metric depends on an extent to which a communication rate of a first of the participants matches a communication rate of a second of the participants, and wherein the assessment data for the conversation include data indicative of one or more assessments of the conversation; and training one or more predictive models to provide one or more assessments of an ongoing conversation based, at least in part, on conversation metric data for the ongoing conversation, wherein training a first of the one or more predictive models comprises fitting the first predictive model to training data including the conversation metric data for the plurality of conversations and at least a portion of the conversation assessment data for the plurality of conversations.
1. A computer-implemented predictive modeling method comprising: obtaining conversation metric data and conversation assessment data for respective conversations included in a plurality of conversations, wherein the metric data for a respective conversation include data indicative of one or more values of one or more metrics for evaluating conversation quality, wherein the one or more metric values are determined based, at least in part, on communications of two or more participants in the conversation, wherein the metrics include a proportionality metric and/or a matching metric, wherein a value of the proportionality metric depends on proportions of communication contributed to the conversation by the two or more participants, wherein a value of the matching metric depends on an extent to which a communication rate of a first of the participants matches a communication rate of a second of the participants, and wherein the assessment data for the conversation include data indicative of one or more assessments of the conversation; and training one or more predictive models to provide one or more assessments of an ongoing conversation based, at least in part, on conversation metric data for the ongoing conversation, wherein training a first of the one or more predictive models comprises fitting the first predictive model to training data including the conversation metric data for the plurality of conversations and at least a portion of the conversation assessment data for the plurality of conversations. 4. The method of claim 1 , wherein the metrics include the proportionality metric, and wherein the one or more metric values include a value of the proportionality metric for the conversation.