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ORIGINAL RESEARCH article

Front. Commun.
Sec. Language Communication
Volume 9 - 2024 | doi: 10.3389/fcomm.2024.1431264

Influence of Gender Dimorphism on Audience Engagement in Podcasts: A Machine Learning Analysis of Dynamic Affective Linguistic and Paralinguistic Features

Provisionally accepted
Willem J. Verbeke Willem J. Verbeke 1*Amita Sharma Amita Sharma 2
  • 1 Erasmus University Rotterdam, Rotterdam, Netherlands
  • 2 Institute of Agri Business Management, Bikaner, Rajasthan, India

The final, formatted version of the article will be published soon.

    Effective communication is a crucial objective for business leaders, educators, and politicians alike. Achieving impactful communication involves not only the selection of appropriate words but also proficiency in their delivery. Previous research has frequently examined linguistic, affective linguistic and paralinguistic features in isolation, thereby overlooking their cumulative effect over time. This study addresses this gap by utilizing a machine learning approach to analyse the dynamic interplay between affective linguistic and paralinguistic features across various episodes of online podcasts.Furthermore, this research incorporates an analysis of gender differences, acknowledging the dimorphic nature of language and speech across genders. Our findings suggest that accounting for gender while examining the dynamic interactions between affective linguistic and paralinguistic features over time, known as emotional volatility, significantly improves the explanatory power for variations in audience engagement, compared to analyses that consider these variables separately.

    Keywords: affective linguistic, paralinguistic, podcasts, Audience engagement, gender dimorphism

    Received: 11 May 2024; Accepted: 09 Sep 2024.

    Copyright: © 2024 Verbeke and Sharma. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Willem J. Verbeke, Erasmus University Rotterdam, Rotterdam, Netherlands

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.