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:
- CNN (Cable News Network) - Higher democratic/left lean.
- FOX (Fox News) - Higher republican/right lean.
- BBC (British Broadcasting Corporation) - Non-American moderate focus.
- NPR (National Public Radio) - American moderate focus.
Click on any of the logos below to visit that site's homepage.
Conclusions
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.