Social Media and Music Industry Dashboard: Streaming Trends, Platform Insights, and Artist Popularity
Dashboard Description

This dashboard explores the dynamic relationship between social media engagement and the music industry, focusing on various aspects such as streaming trends, audio features, and genre preferences across platforms and regions. By examining correlations between social media activity and streaming data, the evolution of song characteristics over time, and regional genre popularity, this dashboard provides actionable insights for artists, labels, and marketers to better understand and adapt to the ever-changing landscape of the music industry.

Description: In this Dygraph I used a total of 3 variables: Release Date, Youtube Views, and TikTok views. I made this graph to display the amount of views that a song would achieve and the possible trends to tell which platform would it be best for an artisit song to gain popularity on.

The trend I found was that overtime, it was best for a song to best gain popularity on TikTok, mostly due to the pandemic and the quick popularity rise of TikTok use worldwide. Overall YouTube has been a more steady platform for new music, making new music views more predictable but overall worse in total views.

Additional Information TikTok has significantly influenced the music industry, driving songs to viral success. For an in-depth look into how TikTok affects the music discovery, visit TikTok and Music Discovery.

Description: The boxplot compares popularity scores for explicit and non-explicit content. The x-axis shows whether the content is explicit (True/False), and the y-axis displays popularity scores (likely 0-100).

Non-explicit content has a wider distribution, with an interquartile range (IQR) of 60-80 and a median score of 70, indicating greater variability in popularity. Explicit content has a higher median score (80) and a narrower IQR (78-82), reflecting more consistent performance, though with a few outliers.

Overall, explicit content is generally more popular and consistent, while non-explicit content exhibits a broader range of outcomes, including both high-performing and less successful examples.

Description: This time plot shows the average trends in danceability, energy, and acousticness of popular songs from 1921 to 2020, using Spotify data. By averaging these features over each year, the visualization highlights broader trends across decades while minimizing the variability of individual songs.

Acousticness began with the highest values but declined sharply in the 1960s. Similarly, energy started low but increased significantly during the same period, peaking at 0.69 in 2010 before beginning to decline.

Danceability has been more stable over the years but has reached its highest levels in the past 20 years, reflecting a growing preference for more danceable music. Since 2015, the rise of social media has played a major role in shaping music trends, favoring songs with higher energy and danceability while contributing to the decline in acousticness. This influence underscores the impact of social media on modern musical preferences.

Yearly Average of Song Elements (ranged from 0-1)
year danceability energy acousticness
2011 0.5598222 0.6712691 0.2393818
2012 0.5716951 0.6698113 0.2361966
2013 0.5788737 0.6564672 0.2419686
2014 0.5895742 0.6534970 0.2376140
2015 0.5910076 0.6334988 0.2468009
2016 0.5999764 0.5928772 0.2802897
2017 0.6122864 0.5867386 0.2899163
2018 0.6649300 0.5905912 0.2719409
2019 0.6442153 0.5787961 0.2892975
2020 0.6730774 0.6119142 0.2473740

Data Source: Spotify-Data 1921-2020

Description: The bar graph highlights the top-streamed songs across different platforms for songs released in 2024, showcasing distinct leaders on each. On Spotify, the highest-streamed song is a cover of Danza Kuduro, while on Pandora, it’s Numb/Encore by Jay-Z, and on SoundCloud, it’s Like That by Future. Although these songs dominate their respective platforms, they also perform well on others. For instance, Numb/Encore ranks as the third highest-streamed song on Spotify, and Like That takes the second spot on Pandora.

The table reveals a similar cross-platform pattern for 2024 releases. For example, Beautiful Things, which appears as the most-playlisted song on Spotify, is also highly ranked on other platforms, placing second on Apple Music and fourth on Amazon Music. This demonstrates that while songs may vary in their top-ranking positions across platforms, strong performers from 2024 often maintain significant popularity across multiple services.

Track Release_Date Apple Music Playlist Count Amazon Playlist Count Spotify Playlist Count
MILLION DOLLAR BABY 2024-04-26 210 114 30716
Not Like Us 2024-05-04 188 111 28113
i like the way you kiss me 2024-03-19 190 172 54331
Houdini 2024-05-31 182 105 7223
Beautiful Things 2024-01-18 280 154 73118
Gata Only 2024-02-02 160 53 40094
Danza Kuduro - Cover 2024-06-09 NA NA 1
BAND4BAND (feat. Lil Baby) 2024-05-23 191 92 10400
I Had Some Help (feat. Morgan Wallen) 2024-05-10 157 114 16219
The Door 2024-06-14 NA 2 2
LUNCH 2024-05-17 244 163 13800
Like That 2024-03-22 153 109 43025
Fortnight (feat. Post Malone) 2024-04-18 221 134 12784
BLUE 2024-05-17 76 33 6499
Espresso 2024-04-12 298 149 24425
Danza Kuduro - Cover 2024-05-21 NA NA 10
TEXAS HOLD ’EM 2024-02-10 159 177 34044
Future 2024-01-10 NA NA 1
we can’t be friends (wait for your love) 2024-03-08 194 126 26203
Numb / Encore 2024-04-12 NA NA 128

Description: The plot is a side-by-side bar chart showing the distribution of streaming numbers for Spotify, YouTube, Pandora, and SoundCloud for the top 10 most popular artists. Each artist’s streaming numbers are broken down by platform, allowing for an easy comparison of platform contributions.

Surprisingly, YouTube, despite being more recognized for its short-video and community-driven format, accounts for the majority of streams for many of these top artists. This emphasizes YouTube’s significant role in music consumption globally, alongside platforms traditionally associated with music streaming like Spotify. Additionally, SoundCloud and Pandora have notably smaller contributions in comparison, highlighting their more niche audience.

This dashboard was created using Quarto in RStudio, and the R Language and Environment.

The datasets used to create this dashboard are below and cal be dowloaded from Kaggle

Software Citations

Arnold J (2024). ggthemes: Extra Themes, Scales and Geoms for ‘ggplot2’. R package version 5.1.0, https://github.com/jrnold/ggthemes, https://jrnold.github.io/ggthemes/.

Bache S, Wickham H (2022). magrittr: A Forward-Pipe Operator for R. R package version 2.0.3, https://CRAN.R-project.org/package=magrittr.

Dancho M, Vaughan D (2023). tidyquant: Tidy Quantitative Financial Analysis. R package version 1.0.7, https://github.com/business-science/tidyquant.

Kunst J (2022). highcharter: A Wrapper for the ‘Highcharts’ Library. R package version 0.9.4, https://CRAN.R-project.org/package=highcharter.

Neuwirth E (2022). RColorBrewer: ColorBrewer Palettes. R package version 1.1-3, https://CRAN.R-project.org/package=RColorBrewer.

R Core Team (2024). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.

Rinker, T. W., Kurkiewicz, D. (2017). pacman: Package Management for R. version 0.5.0. Buffalo, New York. http://github.com/trinker/pacman.

Xie Y (2024). knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.48, https://yihui.org/knitr/.

Yihui Xie (2014). knitr: A Comprehensive Tool for Reproducible Research in R. In Victoria Stodden, Friedrich Leisch, and Roger D. Peng, editors, Implementing Reproducible Computational Research. Chapman and Hall/CRC. ISBN 978-1466561595.

Yihui Xie (2015). Dynamic Documents with R and knitr. 2nd edition. Chapman and Hall/CRC. ISBN 978-1498716963.

Zhu H (2024). kableExtra: Construct Complex Table with ‘kable’ and Pipe Syntax. R package version 1.4.0, https://github.com/haozhu233/kableExtra, http://haozhu233.github.io/kableExtra/.