Adaptation Strategies of Broadcasting Language in New Media Interactive Replies Based on Conversation Analysis Method

DOI

10.2991/978-2-38476-577-5_97How to use a DOI?

Keywords

Conversation Analysis; Broadcasting Language; Adaptation Strategy; New Media; Interactive Communication

Abstract

Against the backdrop of the rapid development of the new media environment, the adaptability of traditional broadcasting language in interactive responses faces significant challenges, necessitating the exploration of new language strategies to enhance communication effectiveness and user engagement. This study, based on Conversation Analysis, integrates the Interactive Alignment Model and Communication Accommodation Theory to construct a comprehensive model of broadcasting language adaptability. The model comprises three levels: first, the sequential turn-regulation layer, which achieves dynamic control of interaction rhythm through the analysis of adjacency pair structures; second, the language style convergence module, which, utilizing an improved CAT mechanism, adjusts tone, register, and style in real time; third, the pragmatic enhancement layer, which combines emotion recognition and keyword salience analysis to optimize the semantic relevance and expressive strength of language output. In addition, the model incorporates a feedback learning mechanism that continuously iterates and refines language adaptation strategies based on user interaction data. Experimental results indicate that this model significantly outperforms existing baseline models in enhancing audience engagement and interaction satisfaction, resulting in an 18.6% increase in audience retention and content relevance ratings.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xinyi Liu
PY  - 2026
DA  - 2026/05/15
TI  - Adaptation Strategies of Broadcasting Language in New Media Interactive Replies Based on Conversation Analysis Method
BT  - Proceedings of the 2026 5th International Conference on Social Sciences and Humanities and Arts (SSHA 2026)
PB  - Atlantis Press
SP  - 963
EP  - 969
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-577-5_97
DO  - 10.2991/978-2-38476-577-5_97
ID  - Liu2026
ER  -