News Analysis Project

Welcome to the News Analysis Project. Our goal as a project team is to analyze the differences between major news sources by looking at the emotionally charged language used within the written text. We originally were focused on how the authors of these articles chose to use emotive parts of speech (adjectives, nouns, verbs, and adverbs) to structure their reports. However, after noticing that quotation played a large role in the structure of the articles, we began to document demographic data of those quoted in order to design more thorough research questions. Our team has been working with articles from these sources listed below, chosen for their ease of web-based access and their popularity:

Click on any of the logos below to visit that site's homepage.

CNN logo Fox News logo BBC logo NPR logo


Through our analysis of the collected articles, we were able to answer several different questions about our sources. We found that FOX and CNN were using the most emotional language, which is what we originally assumed we would see. NPR and BBC showed considerably less, which we also expected, but we did find that there was still a reliance on emotional language. While looking thorough our selected topics, originally thought we would see larger instances of bias with the Woman’s March articles due to the nature of the protests. However, we found that the articles discussing the 2017 election results, exhibited stronger biases. This corresponded with the total number of emotional words, with the election articles showing the most and the march articles second most. Oddly, the articles on the Travel Ban had the least amount of bias where we expected much more. All of our results can be viewed via the Analysis page, which you can reach from the drop down on the menu bar.

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