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

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.