The Impact of Highlighting Subjective Language on Perceived News Trustworthiness

The rise of misinformation and opinionated articles has made understanding how misleading or biased content influences readers an increasingly important problem. While most prior work focuses on detecting misinformation or deceptive language in real time, far less attention has been paid to how such content is perceived by readers, which is an essential component of misinformation’s effectiveness. In this study, we examine whether highlighting subjective sentences in news articles affects perceived trustworthiness. Using a controlled user experiment and 1,334 article-participant ratings, we find that highlighting subjective content produces a modest yet statistically significant decrease in trust, with substantial variation across articles and participants. To explain this variation, we model trust change after highlighting subjective language as a function of article-level linguistic features and reader-level attitudes. Our findings suggest that readers’ reactions to highlighted subjective language are driven primarily by characteristics of the text itself, and that making subjective language explicit plays a role in shaping perceived trustworthiness.