Our main concern in this analysis was to identify the music genres preferred by Spotify users in Romania, as reflected in the composition of the daily charts. Due to the existing diversity of genres and the constant changes in contemporary music, we could not find a generally accepted music taxonomy to use in our analysis. Therefore, we had to create our own genre categorisation. The musical genres operationalised in these analyses resulted from an exhaustive process of data documentation, collection, processing and sorting. This resulted in the following categories

• Hip Hop (2926 songs): in addition to Hip Hop songs, this category also includes songs categorised under the Trap sub-genre;
• Pop (1995 songs);
• Rock (302 songs);
• Electronic / Dance (186 songs);
• Manele (151 songs);
• Other (187 songs): this is a composite category that includes several classic genres (Latin, R&B, Country, Folk, Jazz) as well as sub-genres that do not fall into these (e.g. Ambient, Lo-Fi, Children’s Music, etc.), but which have not received a significant number of streams and entries to be treated as a main category in its own right.

The delineation of the six main categories was conditioned by several variables, such as the number of songs included in these rankings, the number of streams of these songs, or the membership of sub-genres or genre mergers in which these songs were categorised within the classical genres.

The proposed classification is to some extent limited by its reductionism to the six categories of music genres. However, we propose this type of categorisation as a relevant starting point to capture broader music consumption trends among users of the Spotify platform in Romania.

The songs in the Spotify charts considered in this analysis fall into several genres and sub-genres. Depending on their specificity, songs were associated with 1 or 2 genres. For example, a Pop song may have Electronic / Dance influences, as in the case of Glass Animals’ ‘Heatwaves’. This puts it in both the Pop genre and the Electronic / Dance sub-genre.

For a more nuanced understanding of the diversity and fusion between genres, an extended classification of 12 genres (Pop, Hip-Hop, Trap, Electronic/Dance, Rock, Rock, Jazz, Folk, Folk, Country, R&B, Latin, Manele, Other) has emerged. This type of categorisation makes the connections between genres and sub-genres more concrete.

In the visualisation below, the connections between genres are shown as bands connecting the main genre to the sub-genres. The width of the arrows is proportional to the number of songs that fall into that main genre and its subgenres.

The data analysis highlighted the distinction between artists, i.e. local productions, and foreign artists and productions. Based on this criterion of origin, a new type of classification of songs was outlined.

The Spotify weekly charts in Romania analysed in this publication are mainly composed of international tracks. About 73% (4213 songs) of the total sum of these charts represent productions by foreign artists, and only 27% (1534 songs) represent Romanian music. This indicates a preference among the users included in the study for foreign music over local productions.

Even though the number of international songs in the sample is almost 3 times higher than the number of Romanian songs, there is only a 20% difference between the total number of streams for international and Romanian songs. The example of Manele is the most eloquent in this respect. Although there are only 151 manele songs in the sample, the total number of streams for the whole genre is the third highest of all genres. The streams made by Romanian songs represent 40% of the total streams recorded by the songs in the dataset.

Spotify measures each song against a set of sonic and thematic characteristics. The app uses these features to classify all the complexities found in a song into universal categories, mainly for the purpose of predicting a user’s taste. If a song meets a certain number of criteria based on user feedback, a new song will appear on the client’s “Discover Weekly” playlist. By examining these metrics that Spotify identifies, we can begin to understand what characteristics are associated with promoting music that is considered popular.

These characteristics include, but are not limited to: danceability, energy, speechiness, acousticness, instrumentalness, and valence.

Spotify measurement parameters

Each parameter is measured on a scale of 0.0 to 1.0.

• Danceability – how danceable a song is based on a combination of musical elements. Songs with a danceable rhythm score high.
• Energy – a perceptual measure of the intensity and activity of a song. Songs that are typically fast, loud and boisterous score high. For example, death metal has high energy, while a Bach prelude scores low on this scale.
• Speechiness – detects the presence of spoken words in a song. Values between 0.33 and 0.66 describe tracks that may contain both music and speech, either in sections or layered, including cases such as rap music.
• Acousticness – Songs with mainly acoustic rather than electronic instrumentation score high.
• Instrumentalness: Predicts whether a song contains no vocals. Scores above 0.5 are considered to be instrumental pieces, but confidence increases as the score approaches 1.0.
• Valence – how happy a song makes you feel. A measure of the musical positivity conveyed by a song. Songs with high valence sound more positive (happy, cheerful, euphoric), while songs with low valence sound more negative (sad, depressed, angry).