Click here to view my portfolio.
Last.fm is an online music database, a music recommender system, and a social networking service, which was founded in the days when MSN, Myspace, and Runescape were still a thing. In general, the website offers a plugin for you to install on your PC and phone, which can track your listening behaviour. One listen, a scrobble, is then transferred (or “scrobbled”) to the database and displayed on your personal profile. Based on the collected data, it could also recommend you new music to discover or connect you to people with similar music taste. Although the social aspects have been watered down, I’ve still been using their service ever since June 2011 (my profile). With a vast amount of data up for grabs, it would be a waste to leave the data as it is. That is why I’m interested in learning more about how my listening has changed over the years.
As of December 31st of 2020, I have approximately over 97.000 registered scrobbles and 24.000 unique tracks over the course of ten years. The size is too big for the scope of this course, so I will be limiting to a set number of top tracks each year. This makes it easier to explore the data without losing much overview of my general listening behaviour.
My corpus will be divided in years from June 2011 to the end of 2020. According to a NYTimes-article, our musical taste is established during our (formative) teenage years. If that is the case, I’d expect that a certain music style from my teenage years would show up throughout my corpus. Apart from that, I still expect changes in my music preferences, as I grow older.
I used Spotlistr and Soundiiz to transfer 60 tracks per year from my last.fm profile to Spotify. As I’ve been listening to albums more than separate songs at some point in life, I decided to grab top 10 tracks and the remaining 50 tracks between #11-100 at random to broaden the scope. Sometimes the tool didn’t pick the correct track due to changes in the metadata, for which I adjusted manually. Examples include band name changes, such as ‘Viet Cong’ to ‘Preoccupations’ and ‘Andrew Jackson Jihad’ to ‘AJJ’. If a top 10 song was missing, then the next song was selected (#11 and so on). I also removed tracks that are considered as intros or interludes.