How Spotify’s Algorithm Works
Spotify’s algorithm is designed to help users discover new music that they might enjoy based on their listening history and preferences. According to “The Music Recommendation System at Spotify,” published in the Journal of New Music Research in 2014, the algorithm also incorporates explicit feedback from users (e.g., thumbs up/down) and adapts to changes in a user’s listening habits over time. One way in which Spotify’s recommendation algorithm limits musical exploration is by reinforcing users’ existing preferences. The algorithm considers a user’s listening history and suggests music that is like what the user has previously listened to. This can lead to a “bubble” effect, where the user is only exposed to music that is like what they already know and like, rather than being introduced to new and diverse music.
Another way in which the algorithm limits musical exploration is by prioritizing popular music over more niche or underground genres. Because the algorithm is designed to maximize user engagement, it may prioritize music that is more mainstream and widely appealing over more niche or experimental genres. This can limit the ability of users to discover new and interesting music that falls outside of the mainstream.
One significant limitation of Spotify’s recommendation algorithm is the “cold start problem” in music recommendation, first documented in “On the Cold Start Problem in Music Recommendation” (published in the Journal of New Music Research in 2016). The “cold start problem” refers to the difficulty of making accurate recommendations for users who have limited listening history or whose listening habits are not well-represented in the data used to train the recommendation system. Spotify has attempted to address this problem through a variety of approaches, including content-based filtering, social recommendation, and hybrid approaches that combine collaborative and content-based filtering. Content-based filtering may not be the best solution since it relies on the availability and accuracy of metadata about the music such as the genre, artist and lyrics, which may not always be reliable or complete. Social recommendation relies on the existence of a sufficient number of users with similar listening habits, which may not be the case for all users. Hybrid approaches may be more accurate but may also require more data and computational resources.
An example of a setback of Spotify’s algorithm is my personal recommended tab at the bottom of my main spotify playlist:
The problem with these recommendations is that all of these songs besides two are already on this exact playlist, and the two that are not in my playlist, I have already listened to. My personal song recommendations from Spotify prove how poor the algorithm is at introducing new music to listeners.
How Spotify Should Improve the Algorithm
. A potential way to improve the music discovering experience on Spotify would be to incorporate more diverse sources of input into the recommendation algorithm. For example, the algorithm could consider a user’s location, the time of day, and their current activity, in addition to their listening history and preferences. This could help the algorithm suggest music that is more relevant to the user’s current situation and mood and could introduce them to new and interesting music that they might not have discovered otherwise.
Another potential improvement would be to incorporate more diverse sources of music into the algorithm. Currently, the algorithm primarily suggests music from popular, mainstream artists. By incorporating more diverse and independent artists, the algorithm could introduce users to a wider range of music and help them discover new and interesting artists that they might not have heard of otherwise.
Additionally, it may be helpful to allow users to have more control over the recommendations they receive. For example, users could be given the option to choose which genres or artists they want to explore, or to specify which types of music they are interested in discovering. This could help the algorithm provide more personalized and relevant recommendations and could give users a greater sense of control over their music discovery experience.
How to Beat Spotify’s Rigid Algorithm
If you are looking for a place to find new and interesting music that may be completely different than what you are accustomed to, a random approach is a great way to start. To start this randomized journey, visit the website Everynoise. Once on the homepage, simply hit scan and listen to a sample of the genre it selects for you! If you like the sound, click the two arrows on the left of the genre name to explore more of the genre. If you do not like the sound of the genre, the website will simply move on to another genre after the 10 second sample is played.
If complete randomness makes you uneasy, choose your favorite popular genre of music and follow these steps:
- If you want to discover new music that is different from pop:
- Consider exploring other genres within popular music, such as rock, hip hop, or electronic dance music
- Look for music from countries or regions that have a rich tradition of pop music that is different from the mainstream pop sound in your own country ( Latin pop, K-pop, Arabic pop)
- Check out music from indie or underground artists who may be less mainstream and more experimental in their sound
- Consider looking for music that incorporates elements of other genres or styles, such as folk, jazz, or world music
- If you want to discover new music that is different from rock:
- Explore other genres within rock, such as metal, punk, or alternative rock
- Look for music from countries or regions that have a strong tradition of rock music that is different from the mainstream rock sound in your own country ( Japanese rock, African rock, Arabic rock)
- Consider checking out genres that are influenced by rock but have a distinct sound, such as blues, folk, or Americana
- Look for music that incorporates elements of other genres or styles, such as electronic, hip hop, or world music
- If you want to discover new music that is different from hip hop:
- Explore other genres within hip hop, such as rap, trap, or grime
- Look for music from countries or regions that have a strong tradition of hip hop that is different from the mainstream hip hop sound in your own country (Latin hip hop, Asian hip hop, African hip hop)
- Check out genres that are influenced by hip hop but have a distinct sound, such as reggae, dancehall, or funk
- Look for music that incorporates elements of other genres or styles, such as electronic, rock, or world music
- If you want to discover new music that is different from (EDM):
- Explore other genres within EDM, such as techno, house, or trance
- Look for music from countries or regions that have a strong tradition of EDM that is different from the mainstream EDM sound in your own country
- Check out genres that are influenced by EDM but have a distinct sound, such as ambient, experimental electronic, or noise
- Look for music that incorporates elements of other genres or styles, such as rock, hip hop, or world music
No matter how different the new music you explore is from what you are used to, you should feel proud of yourself for stepping out of the comfort zone that Spotify provides for you!
