Mohammed El-Astal

A Move Analysis of a ChatGPT-4o-Generated News Release: Insights from a Quasi-Experimental Study in the Digital Transformation Era

Introduction

A move analysis of a chatgpt-4o-generated news release: insights from a quasi-experimental study in the digital transformation era. Assess ChatGPT-4o's news release quality via rhetorical move analysis in a quasi-experimental study. Offers insights for PR educators & practitioners in the digital transformation era, recommending AI training.

Abstract

This quasi-experimental paper aims to assess the quality of news releases generated by ChatGPT-4o. To that end, I purposively selected a short news release from PR Newswire—a global press release distribution partner. The news release was divided into sentences and fed to ChatGPT-4o, which was prompted to generate a news release based on the provided information. To orient analysis, the study proposed a rhetorical move model comprising three main constant (obligatory) moves—headline, lead, and body—and optional sub-moves within the lead and body that may vary from one situation to another. This paper recommends customized news release training for ChatGPT. The paper is expected to be of considerable value and benefit to PR educators and practitioners, presenting both (a) a cover-all prompt model for producing news releases using ChatGPT and (b) a model example for manually crafting news releases. Ultimately, the paper lays the groundwork for future research on the capabilities of other AI writing tools and their applications to various genres.

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