  While there is an abundance of popular writing targeted to podcast creators
on how to speak in ways that engage their listeners, there has been little
data-driven analysis of podcasts that relates linguistic style with listener
engagement. In this paper, we investigate how various factors -- vocabulary
diversity, distinctiveness, emotion, and syntax, among others -- correlate with
engagement, based on analysis of the creators' written descriptions and
transcripts of the audio. We build models with different textual
representations, and show that the identified features are highly predictive of
engagement. Our analysis tests popular wisdom about stylistic elements in
high-engagement podcasts, corroborating some aspects, and adding new
perspectives on others.
