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TikTok Viral Songs 2019
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About
The most popular songs on TikTok during 2019. As TikTok experienced significant growth and popularity in 2019, this collection offers a unique opportunity to analyse the types of music promoted by this social media platform and embraced by its user base. It includes essential information, such as track and artist names, alongside advanced musical characteristics like tempo and time signature, enabling in-depth analysis of audio features.
Columns
- track_name: The name of the musical track.
- artist_name: The name of the artist who performed the track.
- artist_pop: A numerical indicator of the artist's popularity, ranging from 0 to 93.
- album: The name of the album to which the track belongs.
- track_pop: A numerical indicator of the track's popularity, ranging from 0 to 90.
- danceability: A measure from 0.0 to 1.0 describing how suitable a track is for dancing, based on various musical elements. A higher value indicates greater danceability.
- energy: A measure from 0.0 to 1.0 representing the perceived intensity and activity of the track. Higher values suggest faster, louder, and noisier tracks.
- loudness: The overall loudness of the track in decibels (dB), averaged across its duration. Values typically range between -60 and 0 dB.
- mode: Indicates the modality (major or minor) of the track, with 1 representing major and 0 representing minor.
- key: The musical key of the track, represented by integers mapping to standard Pitch Class notation (e.g., 0 = C). A value of -1 indicates no key was detected.
- speechiness: Detects the presence of spoken words. Values above 0.66 suggest entirely spoken-word tracks, while values between 0.33 and 0.66 may contain both music and speech. Values below 0.33 are typically music.
- acousticness: A confidence measure from 0.0 to 1.0 indicating whether the track is acoustic. A value of 1.0 signifies high confidence in its acoustic nature.
- instrumentalness: Predicts whether a track contains no vocals. Higher values (closer to 1.0) suggest a greater likelihood of the track being instrumental.
- liveness: Detects the presence of an audience. A value above 0.8 strongly indicates that the track was performed live.
- valence: A measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track. High valence tracks sound happy or cheerful, while low valence tracks sound sad or angry.
- tempo: The estimated tempo of the track in beats per minute (BPM), reflecting the speed or pace of the music.
- time_signature: An estimated time signature, indicating how many beats are in each bar. It ranges from 3 to 7 (e.g., "3/4" to "7/4").
- duration_ms: The duration of the track in milliseconds.
Distribution
The dataset is available as a CSV file, named
TikTok_songs_2019.csv. It comprises 223 distinct records (rows) and 18 columns, with a total file size of 27.91 kB. All data points within the dataset are valid, with no missing values reported across any of the columns.Usage
This dataset is ideally suited for various analytical tasks, including understanding the dynamics of viral music on social media platforms. It can be used by researchers to investigate the characteristics that contribute to a song's popularity, to develop models predicting music trends, or to study the correlation between specific audio features and listener engagement. Furthermore, it could aid in the development of music recommendation algorithms or provide insights for cultural studies focused on digital music consumption patterns.
Coverage
The data encompasses popular songs on TikTok specifically within the year 2019. The provided information does not specify geographic or demographic coverage.
License
CC0: Public Domain
Who Can Use It
- Music Industry Analysts: For identifying market trends and understanding consumer preferences in popular music.
- Social Media Researchers: To explore the impact of platforms like TikTok on music discovery, promotion, and cultural dissemination.
- Data Scientists and Machine Learning Engineers: For building and testing models related to music recommendation, genre classification, or virality prediction.
- Academics and Students: Conducting studies on popular culture, digital media, and audio features in music.
- Content Creators and Marketers: To inform strategies for engaging audiences with music on digital platforms.
Dataset Name Suggestions
- TikTok Viral Songs 2019
- 2019 TikTok Music Analysis
- Popular TikTok Tracks: A 2019 Study
- TikTok Audio Features 2019
- Music Trends on TikTok (2019)
Attributes
Original Data Source: TikTok Viral Songs 2019
QUALITY