This data set contains frequency counts of target words in 5 million news and opinion articles from 3 popular newspapers in Spain: El Pa��s, El Mundo and ABC. The target words are listed in the associated manuscript and are mostly words that denote some type of prejudice. A few additional words not denoting prejudice are also available since they are used in the manuscript for illustration purposes. The textual content of news and opinion articles from the outlets listed in Figure 1 of the main manuscript is available in the outlet's online domains and/or public cache repositories such as Google cache (https://webcache.googleusercontent.com), The Internet Wayback Machine (https://archive.org/web/web.php), and Common Crawl (https://commoncrawl.org). We used derived word frequency counts from original sources. Textual content included in our analysis is circumscribed to articles headlines and main body of text of the articles and does not include other article elements such as figure captions. Targeted textual content was located in HTML raw data using outlet specific xpath expressions. Tokens were lowercased prior to estimating frequency counts. To prevent outlets with sparse text content for a year from distorting aggregate frequency counts, we only include outlet frequency counts from years for which there is at least 1 million words of article content from an outlet. Yearly frequency usage of a target word in an outlet in any given year was estimated by dividing the total number of occurrences of the target word in all articles of a given year by the number of all words in all articles of that year. This method of estimating frequency accounts for variable volume of total article output over time. The list of compressed files in this data set is listed next: -analysisScripts.rar contains the analysis scripts used in the main manuscript -targetWordsInArticlesCounts.rar contains counts of target words in outlets articles as well as total counts of words in articles Usage Notes In a small percentage of articles, outlet specific XPath expressions can fail to properly capture the content of the article due to the heterogeneity of HTML elements and CSS styling combinations with which articles text content is arranged in outlets online domains. As a result, the total and target word counts metrics for a small subset of articles might not be precise. To conclude, in a data analysis of millions of news articles, we cannot manually check the correctness of frequency counts for every single article and hundred percent accuracy at capturing articles��� content is elusive due to the small number of difficult to detect boundary cases such as incorrect HTML markup syntax in online domains. Overall however, we are confident that our frequency metrics are representative of word prevalence in print news media content (see Figure 2 of main manuscript for supporting evidence).