Trust – and the lack of it – has become the metric of choice when discussing the alienation individuals feel regarding news organizations. When we consider what the metric is telling us, the picture is undeniably grim.

In an October 2023 poll, Gallup found that more people said they had no trust at all in the media (39%) than those that said they had a great deal of trust (32%). Increasing accountability and transparency are oft-cited prescriptions news organizations focus on to build trust.

Getting to the root of trust issues

However, many people say that the reasons they don’t trust the media include a failure to cover both sides of an issue and the perception that journalists have a political bias, particularly a liberal bias. The Gallup poll reflected a 47% trust gap between Democrats (58%) and Republicans (11%). That said, trust among Democrats is falling significantly for the same reason that it has plummeted for Republicans: a perception of bias, in this case, a conservative bias. The nation’s political polarization is further driving down media trust.

It is understandable that media organizations believe that audience perception of bias can be addressed through transparency efforts focused on the way journalists report and disseminate the news. Unfortunately, there’s a fundamental element of storytelling that may have a much bigger impact on the appearance of bias: word choice.

It’s difficult to address issues of bias when people fail to see themselves reflected in the words journalists use. Language is not merely a tool for communication but a reflection of positioning and perspective, bias and blame. Academic studies show that trust and distrust are encoded in the very language choices we make.

Research we’ve been conducting at the University of Florida’s College of Journalism and Communications is identifying patterns of common language usage in coverage of controversial and potentially divisive subjects that could drive wedges and further damage trust. It is possible that, by recoding words away from inherent biases and towards authentic language people use to describe their experiences, we may find a pathway that engenders trust.

While the pursuit of trust is indeed a noble one, it feels more ambitious than the current climate allows. Therefore, journalists should ask the question: Is trust entirely in my control? And if not, what is? Our work has steered us toward focusing on what can be controlled: authenticity, intentionality and precision. We believe these elements can serve as the building blocks that lead to greater trust.

Based on that work, we’re developing a machine-learning tool journalists can use to identify potentially biased language and use that feedback to make more intentional word choices. The tool, called Authentically, is aimed at equipping journalists with the insights to make informed decisions in their writing. Authentically is currently in the alpha stage of development and we’re working with newsroom partners to test functionality.

When complete, the tool will operate in real time to flag words that merit more careful consideration. By providing a more robust context to the connotations of language, journalists are given the opportunity to ask themselves: Is this really what I meant to say? Does this accurately represent the events I’m describing? Is this language biased?

Word choices and perceived bias

Throughout our investigation of multiple news topics, common patterns of use emerged. In our analysis of abortion coverage, the data indicated that words conveying a sense of pride, such as “proudly,” “unapologetically” and “adamantly” frequently preceded the pro-life label, whereas the pro-choice label was frequently preceded by words indicating a sense of necessity or urgency, such as “necessarily,” “increasingly” and “relentlessly.” While these differences might appear subtle, they raise critical questions: what is being communicated when the language used around one position consistently denotes an undertone of morality while the other suggests one of urgency?

In examining coverage of racial justice protests, specifically regarding the murder of George Floyd in 2020, the findings spoke for themselves. The verbs used to describe protest actions repeatedly drew comparisons to fire or destruction, such as “spark,” “fuel,” “erupt,” “ignite,” “trigger” and “flare.” Is the recurrent use of this fiery language a deliberate choice, or is it a subconscious pattern of bias? What impact does that have on the perception of these demonstrations and of the people participating in them?

As concerns and polarizations regarding the climate grow, so does the importance to be conscious of our language choices. Verbs used with the term “global warming” appear to have a more neutral focus on the general effects, such as “occur” and “bring,” while verbs used with the term “climate change” delve deeper into the speed, intensity and potential ramifications of ongoing environmental shifts, such as “alter,” “fuel” and “accelerate.” Does the language journalists use – even when the differences are subtle – help convey the urgency of a climate emergency, and therefore shape perceptions?

While the foundational tenants of journalism remain core to audience trust, words matter. Our research has illustrated to us the pivotal role of authenticity, intentionality and precision in beginning to bridge the gap between the intention of the journalist and the ways their stories are received by the public.

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About the authors

Janet Coats is the Managing Director of the Consortium on Trust in Media and Technology at the University of Florida’s College of Journalism and Communications. She spent 25 years as a journalist and a decade as a media consultant before moving to higher education.

Kendall Moe is the Senior Project Manager and Researcher for the Authentically project and has conducted the language analysis described in this story. She has an undergraduate degree in linguistics and a master’s degree in special education from the University of Florida.