# Pitchfork Music Reviews Dataset

This repository contains the code and dataset for scraping music reviews from Pitchfork.

## Dataset Overview

The Pitchfork Music Reviews dataset is a collection of music album reviews from the Pitchfork website. Each entry in the dataset represents a single review and includes the following attributes:

-   `artist`: The artist of the album.
-   `album`: The name of the album.
-   `year_released`: The year the album was released.
-   `rating`: The rating given to the album by the reviewer.
-   `small_text`: A short snippet from the review.
-   `review`: The full text of the review.
-   `reviewer`: The name of the reviewer.
-   `genre`: The genre(s) of the album.
-   `label`: The record label that released the album.
-   `release_date`: The release date of the review.
-   `album_art_url`: The URL of the album art.

## Usage

This dataset is publicly available for research. The data is provided 'as is', and you assume full responsibility for any legal or ethical issues that may arise from the use of the data.

## Scraping Process

The dataset was generated by scraping the Pitchfork website. The Python script uses the `requests` and `BeautifulSoup` libraries to send HTTP requests to the website and parse the resulting HTML content.

The script saves the data in an SQLite database and can also export the data to a CSV file. Duplicate entries are avoided by checking for existing entries with the same artist and album name before inserting new ones into the database.

## Potential Applications

This dataset can be used for a variety of research purposes, such as:

- Music information retrieval
- Text mining and sentiment analysis
- Music recommendation systems
- Music trend analysis

## Acknowledgments

The dataset is sourced from [Pitchfork](https://pitchfork.com/), a website that publishes daily reviews, features, and news stories about music.

## License

Please ensure you comply with Pitchfork's terms of service before using or distributing this data.
task_categories:summarization task_categories:text-generation task_categories:question-answering size_categories:10K<n<100K language:en license:mit music region:us
{"language": ["en"], "license": "mit", "size_categories": ["10K<n<100K"], "task_categories": ["summarization", "text-generation", "question-answering"], "tags": ["music"]}
TAGS
#task_categories-summarization #task_categories-text-generation #task_categories-question-answering #size_categories-10K<n<100K #language-English #license-mit #music #region-us 

# Pitchfork Music Reviews Dataset

This repository contains the code and dataset for scraping music reviews from Pitchfork.

## Dataset Overview

The Pitchfork Music Reviews dataset is a collection of music album reviews from the Pitchfork website. Each entry in the dataset represents a single review and includes the following attributes:

-   'artist': The artist of the album.
-   'album': The name of the album.
-   'year_released': The year the album was released.
-   'rating': The rating given to the album by the reviewer.
-   'small_text': A short snippet from the review.
-   'review': The full text of the review.
-   'reviewer': The name of the reviewer.
-   'genre': The genre(s) of the album.
-   'label': The record label that released the album.
-   'release_date': The release date of the review.
-   'album_art_url': The URL of the album art.

## Usage

This dataset is publicly available for research. The data is provided 'as is', and you assume full responsibility for any legal or ethical issues that may arise from the use of the data.

## Scraping Process

The dataset was generated by scraping the Pitchfork website. The Python script uses the 'requests' and 'BeautifulSoup' libraries to send HTTP requests to the website and parse the resulting HTML content.

The script saves the data in an SQLite database and can also export the data to a CSV file. Duplicate entries are avoided by checking for existing entries with the same artist and album name before inserting new ones into the database.

## Potential Applications

This dataset can be used for a variety of research purposes, such as:

- Music information retrieval
- Text mining and sentiment analysis
- Music recommendation systems
- Music trend analysis

## Acknowledgments

The dataset is sourced from Pitchfork, a website that publishes daily reviews, features, and news stories about music.

## License

Please ensure you comply with Pitchfork's terms of service before using or distributing this data.
# Pitchfork Music Reviews Dataset

This repository contains the code and dataset for scraping music reviews from Pitchfork. ## Dataset Overview

The Pitchfork Music Reviews dataset is a collection of music album reviews from the Pitchfork website. Each entry in the dataset represents a single review and includes the following attributes:

-   'artist': The artist of the album.
-   'album': The name of the album.
-   'year_released': The year the album was released.
-   'rating': The rating given to the album by the reviewer.
-   'small_text': A short snippet from the review.
-   'review': The full text of the review.
-   'reviewer': The name of the reviewer.
-   'genre': The genre(s) of the album.
-   'label': The record label that released the album.
-   'release_date': The release date of the review.
-   'album_art_url': The URL of the album art. ## Usage

This dataset is publicly available for research. The data is provided 'as is', and you assume full responsibility for any legal or ethical issues that may arise from the use of the data. ## Scraping Process

The dataset was generated by scraping the Pitchfork website. The Python script uses the 'requests' and 'BeautifulSoup' libraries to send HTTP requests to the website and parse the resulting HTML content.

The script saves the data in an SQLite database and can also export the data to a CSV file. Duplicate entries are avoided by checking for existing entries with the same artist and album name before inserting new ones into the database. ## Potential Applications

This dataset can be used for a variety of research purposes, such as:

- Music information retrieval
- Text mining and sentiment analysis
- Music recommendation systems
- Music trend analysis ## Acknowledgments

The dataset is sourced from Pitchfork, a website that publishes daily reviews, features, and news stories about music. ## License

Please ensure you comply with Pitchfork's terms of service before using or distributing this data.
TAGS
#task_categories-summarization #task_categories-text-generation #task_categories-question-answering #size_categories-10K<n<100K #language-English #license-mit #music #region-us 
 # Pitchfork Music Reviews Dataset

This repository contains the code and dataset for scraping music reviews from Pitchfork. ## Dataset Overview

The Pitchfork Music Reviews dataset is a collection of music album reviews from the Pitchfork website. Each entry in the dataset represents a single review and includes the following attributes:

-   'artist': The artist of the album.
-   'album': The name of the album.
-   'year_released': The year the album was released.
-   'rating': The rating given to the album by the reviewer.
-   'small_text': A short snippet from the review.
-   'review': The full text of the review.
-   'reviewer': The name of the reviewer.
-   'genre': The genre(s) of the album.
-   'label': The record label that released the album.
-   'release_date': The release date of the review.
-   'album_art_url': The URL of the album art. ## Usage

This dataset is publicly available for research. The data is provided 'as is', and you assume full responsibility for any legal or ethical issues that may arise from the use of the data. ## Scraping Process

The dataset was generated by scraping the Pitchfork website. The Python script uses the 'requests' and 'BeautifulSoup' libraries to send HTTP requests to the website and parse the resulting HTML content.

The script saves the data in an SQLite database and can also export the data to a CSV file. Duplicate entries are avoided by checking for existing entries with the same artist and album name before inserting new ones into the database. ## Potential Applications

This dataset can be used for a variety of research purposes, such as:

- Music information retrieval
- Text mining and sentiment analysis
- Music recommendation systems
- Music trend analysis ## Acknowledgments

The dataset is sourced from Pitchfork, a website that publishes daily reviews, features, and news stories about music. ## License

Please ensure you comply with Pitchfork's terms of service before using or distributing this data.
passage: TAGS
#task_categories-summarization #task_categories-text-generation #task_categories-question-answering #size_categories-10K<n<100K #language-English #license-mit #music #region-us 
# Pitchfork Music Reviews Dataset

This repository contains the code and dataset for scraping music reviews from Pitchfork.## Dataset Overview

The Pitchfork Music Reviews dataset is a collection of music album reviews from the Pitchfork website. Each entry in the dataset represents a single review and includes the following attributes:

-   'artist': The artist of the album.
-   'album': The name of the album.
-   'year_released': The year the album was released.
-   'rating': The rating given to the album by the reviewer.
-   'small_text': A short snippet from the review.
-   'review': The full text of the review.
-   'reviewer': The name of the reviewer.
-   'genre': The genre(s) of the album.
-   'label': The record label that released the album.
-   'release_date': The release date of the review.
-   'album_art_url': The URL of the album art.## Usage

This dataset is publicly available for research. The data is provided 'as is', and you assume full responsibility for any legal or ethical issues that may arise from the use of the data.## Scraping Process

The dataset was generated by scraping the Pitchfork website. The Python script uses the 'requests' and 'BeautifulSoup' libraries to send HTTP requests to the website and parse the resulting HTML content.

The script saves the data in an SQLite database and can also export the data to a CSV file. Duplicate entries are avoided by checking for existing entries with the same artist and album name before inserting new ones into the database.## Potential Applications

This dataset can be used for a variety of research purposes, such as:

- Music information retrieval
- Text mining and sentiment analysis
- Music recommendation systems
- Music trend analysis