Researchers from Israel’s Tel Aviv University and Ariel University are demonstrating that three songs from an individual’s playlist is all that is necessary to identify the listener who selected the songs.

The researchers split 150 undergraduate students into four different groups and instructed participants to create their own playlists. Once complete, the researchers used an in-house mathematical model to identify participants from each group based on just three of their song selections, which spanned various musical artists and genres.

According to the results, researchers identified participants based on their musical tastes alone with a success rate range of 80% to 100%.

Dr. Ori Leshman of Tel Aviv University and Dr. Ron Hirschprung of Ariel University explained: "Music can become a form of characterization, and even an identifier. It provides commercial companies like Google and Spotify with additional and more in-depth information about us as users of these platforms. In the digital world we live in today, these findings have far-reaching implications on privacy violations, especially since information about people can be inferred from a completely unexpected source, which is therefore lacking in protection against such violations. Visiting YouTube is perceived by the ordinary person as an innocuous act, but this study shows that it can reveal a lot about that person. On the other hand, this knowledge can be used as a bridge between people and perhaps in the future lead to the creation of new diagnostic methods and fascinating intervention programs that will make use of people's favorite music."

The research appears in the journal Telematics and Informatics.