Estimates suggest that Apple Music had 95 million subscribers worldwide in June 2024, up by 2 million from the previous year. Launched in 2015 by U.S. tech giant Apple, Apple Music is the second largest music streaming service worldwide, competing with market leader Spotify. Spotify remains market leader While Apple Music is a popular music streaming platform, accounting for 12.6 percent of subscribers worldwide, the 2008 founded streaming service Spotify remains the market leader with a subscriber share of nearly 32 percent. Financially this meant that the Swedish company generated a global revenue of 3.7 billion euros through its Premium accounts in the fourth quarter of 2024 alone.Music streaming overall increasesOverall, music streaming has experienced significant growth over the last decade. Even if the annual growth rate is gradually declining, it still stood at over 7 percent in 2024, becoming the music industry’s main revenue driver and reaching a revenue of 20 billion U.S. dollars worldwide in 2024.

This dataset contains 5,640 user-submitted reviews of major music streaming apps on iOS, gathered from the Apple App Store’s public RSS feed.

Covered applications include: * Apple Music * Spotify * TIDAL * SoundCloud * Deezer * Shazam

Each review includes: * 🌍 country: Reviewer’s regional App Store (e.g., US, GB, JP) * 📝 review: Full text of the review (with title and body) * ⭐ rating: User star rating from 1 to 5 * 🕓 date: Timestamp (ISO format) * 👤 author: Reviewer display name

These reviews were retrieved using Apple’s publicly accessible RSS feed endpoints. No login or scraping was used.

This dataset contains 76,535 real user reviews collected from the Google Play Store across seven popular music streaming applications: Spotify, Apple Music, SoundCloud, TIDAL, Deezer, Shazam, and Google Play Music.

Each review includes: * 🌐 The app name * 📝 The review content * ⭐ A star rating from 1 to 5 * 📱 The app version (if available) * 📅 The date the review was written

This dataset is cleaned (empty or invalid entries removed) but intentionally unaltered in tone, preserving user expressions (including slang, emojis, and punctuation). Total entries: 76,535 Language: Primarily English Date range: Varied (depending on app)

App Reviews

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1842206%2Fd4a6033b6bd31af45d5175d02e697934%2FAPPLEAPPS2.png?generation=1700357122842963&alt=media" alt="">

1. uber-request-a-ride-us- 73787 rows
2. waze-navigation-live-traffic-us- 26260 rows
3. facebook-us- 24200 rows
4. spotify-music-and-podcasts-us- 15580 rows
5. netflix-us- 11760 rows
6. pinterest-us- 10860 rows
7. X-us- 8160 rows
8. tiktok-us- 2542 rows
9. tinder-dating-chat-friends-us- 1060 rows
10. instagram-us- 300 rows

These reviews are from Apple App Store

Usage

This dataset should paint a good picture on what is the public's perception of the apps over the years. Using this dataset, we can do the following

1. Extract sentiments and trends
2. Identify which version of an app had the most positive feedback, the worst.
3. Use topic modelling to identify the pain points of the application.

(AND MANY MORE!)

Note

Images generated using Bing Image Generator

This dataset contains the ground truth data used to evaluate the musical pitch, tempo and key estimation algorithms developed during the AudioCommons H2020 EU project and which are part of the Audio Commons Audio Extractor tool. It also includes ground truth information for the single-eventness audio descriptor also developed for the same tool.

This ground truth data has been used to generate the following documents:

• Deliverable D4.4: Evaluation report on the first prototype tool for the automatic semantic description of music samples
• Deliverable D4.10: Evaluation report on the second prototype tool for the automatic semantic description of music samples
• Deliverable D4.12: Release of tool for the automatic semantic description of music samples

All these documents are available in the materials section of the AudioCommons website.

All ground truth data in this repository is provided in the form of CSV files. Each CSV file corresponds to one of the individual datasets used in one or more evaluation tasks of the aforementioned deliverables. This repository does not include the audio files of each individual dataset, but includes references to the audio files. The following paragraphs describe the structure of the CSV files and give some notes about how to obtain the audio files in case these would be needed.

Structure of the CSV files

All CSV files in this repository (with the sole exception of SINGLE EVENT - Ground Truth.csv) feature the following 5 columns:

1. Audio reference: reference to the corresponding audio file. This will either be a string withe the filename, or the Freesound ID (for one dataset based on Freesound content). See below for details about how to obtain those files.
2. Audio reference type: will be one of Filename or Freesound ID, and specifies how the previous column should be interpreted.
3. Key annotation: tonality information as a string with the form "RootNote minor/major". Audio files with no ground truth annotation for tonality are left blank. Ground truth annotations are parsed from the original data source as described in the text of deliverables D4.4 and D4.10.
4. Tempo annotation: tempo information as an integer representing beats per minute. Audio files with no ground truth annotation for tempo are left blank. Ground truth annotations are parsed from the original data source as described in the text of deliverables D4.4 and D4.10. Note that integer values are used here because we only have tempo annotations for music loops which typically only feature integer tempo values.
5. Pitch annotation: pitch information as an integer representing the MIDI note number corresponding to annotated pitch's frequency. Audio files with no ground truth pitch for tempo are left blank. Ground truth annotations are parsed from the original data source as described in the text of deliverables D4.4 and D4.10.

The remaining CSV file, SINGLE EVENT - Ground Truth.csv, has only the following 2 columns:

• Freesound ID: sound ID used in Freesound to identify the audio clip.
• Single Event: boolean indicating whether the corresponding sound is considered to be a single event or not. Single event annotations were collected by the authors of the deliverables as described in deliverable D4.10.

How to get the audio data

In this section we provide some notes about how to obtain the audio files corresponding to the ground truth annotations provided here. Note that due to licensing restrictions we are not allowed to re-distribute the audio data corresponding to most of these ground truth annotations.

• Apple Loops (APPL): This dataset includes some of the music loops included in Apple's music software such as Logic or GarageBand. Access to these loops requires owning a license for the software. Detailed instructions about how to set up this dataset are provided here.
• Carlos Vaquero Instruments Dataset (CVAQ): This dataset includes single instrument recordings carried out by Carlos Vaquero as part of this master thesis. Sounds are available as Freesound packs and can be downloaded at this page: https://freesound.org/people/Carlos_Vaquero/packs
• Freesound Loops 4k (FSL4): This dataset set includes a selection of music loops taken from Freesound. Detailed instructions about how to set up this dataset are provided here.
• Giant Steps Key Dataset (GSKY): This dataset includes a selection of previews from Beatport annotated by key. Audio and original annotations available here.
• Good-sounds Dataset (GSND): This dataset contains monophonic recordings of instrument samples. Full description, original annotations and audio are available here.
• University of IOWA Musical Instrument Samples (IOWA): This dataset was created by the Electronic Music Studios of the University of IOWA and contains recordings of instrument samples. The dataset is available upon request by visiting this website.
• Mixcraft Loops (MIXL): This dataset includes some of the music loops included in Acoustica's Mixcraft music software. Access to these loops requires owning a license for the software. Detailed instructions about how to set up this dataset are provided here.
• NSynth Dataset Test and Validation sets (NSYT and NSYV): NSynth is a large-scale and high-quality dataset of annotated musical notes built with synthesized sounds by Google's Magenta team. Full dataset description including original annotations and audio files is available here.
• Philarmonia Orchestra Sound Samples Dataset (PHIL): This includes thousands of free, downloadable sound samples specially recorded by Philharmonia Orchestra players. Audio files are freely downloadable from the philarmonia orchestra website.
• Freesound Single Events Dataset (SINGLE EVENT): This includes a selection of Freesound audio clips representing audio signals containing either a single audio event or multiple ones. Original audio files can be retrieved by downloading individual audio clips from Freesound using the ID identifier provided in the CSV file. A similar procedure to that described here could be followed.

Apple Inc. designs, manufactures, and markets smartphones, personal computers, tablets, wearables, and accessories worldwide. The company offers iPhone, a line of smartphones; Mac, a line of personal computers; iPad, a line of multi-purpose tablets; and wearables, home, and accessories comprising AirPods, Apple TV, Apple Watch, Beats products, and HomePod. It also provides AppleCare support and cloud services; and operates various platforms, including the App Store that allow customers to discover and download applications and digital content, such as books, music, video, games, and podcasts. In addition, the company offers various services, such as Apple Arcade, a game subscription service; Apple Fitness+, a personalized fitness service; Apple Music, which offers users a curated listening experience with on-demand radio stations; Apple News+, a subscription news and magazine service; Apple TV+, which offers exclusive original content; Apple Card, a co-branded credit card; and Apple Pay, a cashless payment service, as well as licenses its intellectual property. The company serves consumers, and small and mid-sized businesses; and the education, enterprise, and government markets. It distributes third-party applications for its products through the App Store. The company also sells its products through its retail and online stores, and direct sales force; and third-party cellular network carriers, wholesalers, retailers, and resellers. Apple Inc. was founded in 1976 and is headquartered in Cupertino, California.

The people from Czech are publishing a dataset for the HTTPS traffic classification.

Since the data were captured mainly in the real backbone network, they omitted IP addresses and ports. The datasets consist of calculated from bidirectional flows exported with flow probe Ipifixprobe. This exporter can export a sequence of packet lengths and times and a sequence of packet bursts and time. For more information, please visit ipfixprobe repository (Ipifixprobe).

During research, they divided HTTPS into five categories: L -- Live Video Streaming, P -- Video Player, M -- Music Player, U -- File Upload, D -- File Download, W -- Website, and other traffic.

They have chosen the service representatives known for particular traffic types based on the Alexa Top 1M list and Moz's list of the most popular 500 websites for each category. They also used several popular websites that primarily focus on the audience in Czech. The identified traffic classes and their representatives are provided below:

Live Video Stream Twitch, Czech TV, YouTube Live Video Player DailyMotion, Stream.cz, Vimeo, YouTube Music Player AppleMusic, Spotify, SoundCloud File Upload/Download FileSender, OwnCloud, OneDrive, Google Drive Website and Other Traffic Websites from Alexa Top 1M list