Work

Exploring Language Styles Associated With Scientificness in Health News: A Dual Approach Using Text Mining and Reader Perception Studies

Year: 2025

Type: article

Abstract: This research examines whether language styles in U.S. health news relate to scientificness. Study 1 uses human ratings to train machine learning models that classify sentences as scientific or nonscientific. A text mining approach predicts the proportion of scientific sentences, on the basis of language features. Two style categories emerge: one reflecting ideal professional standards of science journalism (hedging, neutrality, objectivity) and another linked to science complexity (low readability, complexity, formality). Study 2 then tests whether perceptions of these six features influence perceived scientificness and intended outcomes through message experiments.

Source: Science Communication

DOI: 10.1177/10755470251386241

Authors: Chingching Chang, Ying-Ju Chiu, Yu-Ming Hsieh, Hao-Hsuan Wang

Institutions: Research Center for Humanities and Social Sciences, Academia Sinica, Academia Sinica, Institute of Information Science, Academia Sinica

Language: English

Topic: Media Studies and Communication

Subfield: Communication

Field: Social Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $3,900

Funder: National Science Council