What is it about?
We examined the top-grossing romantic comedy (romcom) films of all time from 1980-2019. After narrowing down the list of the top 200 films for various reasons, we cleaned and analyzed the scripts of 188 films to see how the genre changed over these four decades. Our results showed that romcoms are increasingly focusing on characters' romantic lives at the expense of their hobbies, friendships, and any non-romantic relationships. Further, the romantic lives depicted are increasingly troubled, with more hurdles, lies, and deception to be overcome in newer films than in previous decades.
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Why is it important?
As a popular form of media, romcoms have a certain level of influence over peoples' expectations for romance, just as much as they might reflect current cultural understandings of dating and love. Young people in particular look to romcoms and similar media to as a measure of what they should want in their own relationships. It was thus important to analyze the content of this genre more deeply; previous research has examined 40 films over two decades at most, and relied on more qualitative approaches that can't detect the patterns computational analysis can.
Perspectives
Much like any relationship depicted in a romcom, there were many hurdles to overcome in the process of this research. There were many choices made along the way (including time frame, top-grossing cut-off, how to segment films for analysis) which illustrate that even a computational analysis is full of human decisions. Ultimately, the findings were intriguing and led to additional phases of research: analyses of how the trends in content relate to success in film (earnings, awards, popularity), and an experiment examining how audiences react to this content. We hope to have these additional reports published in the near future.
Dr. Melissa M. Moore
University at Buffalo - The State University of New York
Read the Original
This page is a summary of: Big data, actually: Examining systematic messaging in 188 romantic comedies using unsupervised machine learning., Psychology of Popular Media, October 2021, American Psychological Association (APA),
DOI: 10.1037/ppm0000349.
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