I will hold a one-day practical workshop on “Emotions in 50 Years of Pop Song Lyrics: A Text Mining Approach” at the 7th Winter School Fact and Method: Data, Borders and Interpretation in Tartu – Estonia, the 7th of February 2018 (this blog post can give an idea of what we will do). The participation for PhD students is free of charge and, according to the organisers, in some cases, it is possible to reimburse the accommodation. See below a short description of the workshop and some suggested readings.
I am almost leaving after few intense days at the Second Moscow-Tartu Late Summer School on Digital Humanities, where I was invited to give a talk about my research on the cultural dynamics of emotion in fiction (see two papers here and here), and more recently in song lyrics (no paper yet – a blog post documenting the very beginning of the research is here).
I found, thanks to twitter-induced serendipity (others call it procrastination), the lyrics of the songs included in the annual Billboard Top-100 from 1965 to 2015 (i.e., considering a few missing, ~5,000 songs). You can find in GitHub, together with the raw data, some clarifications on how the data were collected, their limitations, etc. plus a pointer to a nice analysis already done.
I uploaded on Open Science Framework (here) a dataset. From the description there:
This dataset contains 1,093 movie scripts collected from the website imsdb.com, each in a separate text file. The file imsdb_sample.txt contains the titles of all movies (corresponding file names are in the form Script_TITLE.txt).
The website was crawled in January 2017. Some scripts are not present as they were missing in imsdb.com or because they were uploaded as pdf files. Please notice that (i) the original scripts were uploaded on the website by individual users, so that they might not correspond exactly to the movie scripts and typos may be present; (ii) html formatting was not consistent in the website, and so neither is the formatting of the resulting text files.
Even considering (i) and (ii), the quality seems good on average and the dataset can be easily used for text-mining tasks.
I recently published, together with Olivier Morin, a paper in Cognition and Emotion: Birth of the cool: a two-centuries decline in emotional expression in Anglophone fiction. The main result is about a clear decrease in the emotional tone in English-language literature, starting plausibly from the XIX century, a decrease driven almost entirely by a decline in the proportion of positive emotion-related words, while the frequency of negative emotion-related words shows little if any decline. In other words, English literature became in the last centuries less “emotional” and, in particular, less “positive”.