"Main political figures were talking about it, so I really thought The New York Times would turn out to be biased," said Dalal, a professor at Columbia's applied analytics program and statistics department. "The rhetoric is all about media bias, so you think there might be some truth to it."

But the study found the opposite: The New York Times does not appear to be biased in its coverage of Trump and in its news coverage generally.

While there's no definitive way to measure what is true and false in the reporting of news, researchers were able to analyze writing style in order to determine whether an article was written more favorably or unfavorably using a system called sentiment analysis, Dalal said.

In order to conduct the analysis, researchers collected 1,058 New York Times articles published over 38 days and paired each with a story from Reuters about the same topic published within the same 24 hours.

"We chose Reuters for this purpose since it is an international news agency with a policy of neutral writing and a customer base of media across the entire political spectrum," the researchers wrote in the study.

Dalal and his team used code packages in R and Python to calculate a sentiment score for each story, which indicates if content is more positive or negative.

For instance, a sentence with words like "happy," "satisfactory," or "good" would be considered favorable, while words like "failure" indicate a negative sentiment, researchers wrote in the study. The codes understand modifiers as well, so a sentence that includes "not happy" would be correctly labeled as unfavorable. 

Results showed that front page stories from both outlets had the same sentiment scores, meaning there was no overall difference in the favorability of front page news between The Times and Reuters. 

The Times tended to be more positive in its coverage of business and slightly more negative in international and national news articles than Reuters.