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

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

Department of Digitalization

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

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.

Original language	English
Title of host publication	PACIS 2023 Proceedings
Editors	Patrick Chau, Jack Jing, Mikko Siponen, Andrew Burton-Jones, Chuan-Hoo Tan, Bo Sophia Xiao
Number of pages	17
Place of Publication	Atlanta, GA
Publisher	Association for Information Systems. AIS Electronic Library (AISeL)
Publication date	2023
Article number	194
Publication status	Published - 2023
Event	The 27th Pacific Asia Conference on Information Systems. PACIS 2023 - Nanchang, China Duration: 8 Jul 2023 → 12 Jul 2023 Conference number: 27 https://pacis2023.aisconferences.org/

Conference

Conference	The 27th Pacific Asia Conference on Information Systems. PACIS 2023
Number	27
Country/Territory	China
City	Nanchang
Period	08/07/2023 → 12/07/2023
Internet address	https://pacis2023.aisconferences.org/

Keywords

Audio platform
Online learning
Linguistic features
Engagement behavior

Access to Document

https://aisel.aisnet.org/pacis2023/194Licence: Unspecified
http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1193&context=pacis2023Licence: Unspecified

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Cite this

Liu, X., Jiang, N., Zhao, H., Lim, E. T. K., & Tan, C.-W. (2023). Describing Your Podcasts: Disentangling the Effects of Linguistic Features in Bolstering Online Learners’ Engagement with Podcasters. In P. Chau, J. Jing, M. Siponen, A. Burton-Jones, C.-H. Tan, & B. S. Xiao (Eds.), PACIS 2023 Proceedings Article 194 Association for Information Systems. AIS Electronic Library (AISeL). https://aisel.aisnet.org/pacis2023/194

Liu, Xiaohui ; Jiang, Na ; Zhao, Haiping et al. / Describing Your Podcasts : Disentangling the Effects of Linguistic Features in Bolstering Online Learners’ Engagement with Podcasters. PACIS 2023 Proceedings. editor / Patrick Chau ; Jack Jing ; Mikko Siponen ; Andrew Burton-Jones ; Chuan-Hoo Tan ; Bo Sophia Xiao. Atlanta, GA : Association for Information Systems. AIS Electronic Library (AISeL), 2023.

@inproceedings{1a4a46c9c98b4406a07f8ece72c40663,

title = "Describing Your Podcasts: Disentangling the Effects of Linguistic Features in Bolstering Online Learners{\textquoteright} Engagement with Podcasters",

abstract = "Despite fierce competition among podcasters, there is a dearth of research that has sought to elucidate the role of podcast description{\textquoteright}s linguistic features in fostering learners{\textquoteright} 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{\textquoteright} 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.",

keywords = "Audio platform, Online learning, Linguistic features, Engagement behavior, Audio platform, Online learning, Linguistic features, Engagement behavior",

author = "Xiaohui Liu and Na Jiang and Haiping Zhao and Lim, {Eric T.K.} and Chee-Wee Tan",

year = "2023",

language = "English",

editor = "Patrick Chau and Jack Jing and Mikko Siponen and Andrew Burton-Jones and Chuan-Hoo Tan and Xiao, {Bo Sophia}",

booktitle = "PACIS 2023 Proceedings",

publisher = "Association for Information Systems. AIS Electronic Library (AISeL)",

note = "The 27th Pacific Asia Conference on Information Systems. PACIS 2023, PACIS2023 ; Conference date: 08-07-2023 Through 12-07-2023",

url = "https://pacis2023.aisconferences.org/",

}

Liu, X, Jiang, N, Zhao, H, Lim, ETK & Tan, C-W 2023, Describing Your Podcasts: Disentangling the Effects of Linguistic Features in Bolstering Online Learners’ Engagement with Podcasters. in P Chau, J Jing, M Siponen, A Burton-Jones, C-H Tan & BS Xiao (eds), PACIS 2023 Proceedings., 194, Association for Information Systems. AIS Electronic Library (AISeL), Atlanta, GA, The 27th Pacific Asia Conference on Information Systems. PACIS 2023, Nanchang, China, 08/07/2023. <https://aisel.aisnet.org/pacis2023/194>

Describing Your Podcasts: Disentangling the Effects of Linguistic Features in Bolstering Online Learners’ Engagement with Podcasters. / Liu, Xiaohui; Jiang, Na; Zhao, Haiping et al.
PACIS 2023 Proceedings. ed. / Patrick Chau; Jack Jing; Mikko Siponen; Andrew Burton-Jones; Chuan-Hoo Tan; Bo Sophia Xiao. Atlanta, GA: Association for Information Systems. AIS Electronic Library (AISeL), 2023. 194.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Describing Your Podcasts

T2 - The 27th Pacific Asia Conference on Information Systems. PACIS 2023

AU - Liu, Xiaohui

AU - Jiang, Na

AU - Zhao, Haiping

AU - Lim, Eric T.K.

AU - Tan, Chee-Wee

N1 - Conference code: 27

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - Audio platform

KW - Online learning

KW - Linguistic features

KW - Engagement behavior

KW - Audio platform

KW - Online learning

KW - Linguistic features

KW - Engagement behavior

M3 - Article in proceedings

BT - PACIS 2023 Proceedings

A2 - Chau, Patrick

A2 - Jing, Jack

A2 - Siponen, Mikko

A2 - Burton-Jones, Andrew

A2 - Tan, Chuan-Hoo

A2 - Xiao, Bo Sophia

PB - Association for Information Systems. AIS Electronic Library (AISeL)

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Y2 - 8 July 2023 through 12 July 2023

ER -