Describing Your Podcasts: Disentangling the Effects of Linguistic Features in Bolstering Online Learners’ Engagement with Podcasters

Xiaohui Liu, Na Jiang, Haiping Zhao, Eric T.K. Lim, Chee-Wee Tan

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review


Despite fierce competition among podcasters, there is a dearth of research that has sought to elucidate the role of podcast description’s linguistic features in fostering learners’ engagement with podcasters on audio platforms. Building on cognitive appraisal theory, we not only posit curvilinear relationships between objective linguistic features (i.e., lexical richness and subjectivity) and online learners’ engagement, but we further postulate readability, a subjective linguistic feature, as having a moderating influence on the abovementioned relationships. To empirically validate our hypotheses, we employ Natural Language Processing algorithms to extract the abovementioned three linguistic features of podcast descriptions from 2,280 educational podcasts obtained from a leading audio platform in China. Analytical results point to inverted U-shaped relationships between lexical richness/subjectivity and engagement. Analysis of moderating effects further revealed that readability steepened the inverted U-shaped relationship between lexical richness and engagement while flattening the relationship between subjectivity and engagement.
TitelPACIS 2023 Proceedings
RedaktørerPatrick Chau, Jack Jing, Mikko Siponen, Andrew Burton-Jones, Chuan-Hoo Tan, Bo Sophia Xiao
Antal sider17
UdgivelsesstedAtlanta, GA
ForlagAssociation for Information Systems. AIS Electronic Library (AISeL)
StatusUdgivet - 2023
BegivenhedThe 27th Pacific Asia Conference on Information Systems. PACIS 2023 - Nanchang, Kina
Varighed: 8 jul. 202312 jul. 2023
Konferencens nummer: 27


KonferenceThe 27th Pacific Asia Conference on Information Systems. PACIS 2023


  • Audio platform
  • Online learning
  • Linguistic features
  • Engagement behavior