Update README.md

README.md

@@ -1,38 +1,40 @@
----
-license: mit
-tags:
-- Software Analysis
-pretty_name: Mac App Store Applications Metadata
-size_categories:
-- 10K<n<100K
-language:
-- en
-- de
----
+---
+license: mit
+tags:
+- Software Analysis
+pretty_name: Mac App Store Applications Metadata
+size_categories:
+- 10K<n<100K
+language:
+- en
+- de
+---
 
 # Dataset Card for Macappstore Applications Metadata
 
 <!-- Provide a quick summary of the dataset. -->
 Mac App Store Applications Metadata sourced by the public API.
 
+
+- **Curated by:** [MacPaw Inc.](https://huggingface.co/MacPaw)
+<!---- **Funded by [optional]:** [More Information Needed] -->
+<!--- **Shared by [optional]:** [MacPaw Inc.](https://huggingface.co/MacPaw) -->
+- **Language(s) (NLP):** Mostly EN, DE
+- **License:** [More Information Needed]
+
 ## Dataset Details
 
 This data aims to cover our internal company research needs and start collecting and sharing the macOS app dataset since we have yet to find a suitable existing one.
+Full application metadata was sourced by the public iTunes search API for the US, Germany, and Ukraine between December 2023 and January 2024.
 
-Full application metadata for over 87,000 samples was sourced by the public iTunes search API for the US, Germany, and Ukraine between December 2023 and January 2024.
+The data is organized into 43 columns ranging from such essential details as app names, descriptions, and genres, along with release and version information, user ratings, and asset links. 
 
-For the convenience of further analysis, we present the data as three separate datasets: metadata, release notes, and descriptions.
+<!--For the convenience of further analysis, we present the data as three separate datasets: metadata, release notes, and descriptions.
 
 ### Dataset Description
 
 <!-- Provide a longer summary of what this dataset is. -->
 
-- **Curated by:** [MacPaw Inc.](https://huggingface.co/MacPaw)
-<!---- **Funded by [optional]:** [More Information Needed] -->
-<!--- **Shared by [optional]:** [MacPaw Inc.](https://huggingface.co/MacPaw) -->
-- **Language(s) (NLP):** Mostly EN, DE
-- **License:** [More Information Needed]
-
 <!-- ### Dataset Sources [optional]
 
 <!-- Provide the basic links for the dataset. -->
@@ -64,28 +66,10 @@ For the convenience of further analysis, we present the data as three separate d
 [More Information Needed]
 -->
 
-## Dataset Structure
+<!--## Dataset Structure
 
 <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
-For the convenience of further analysis, we present the data as three separate datasets.
-
-**Metadata Dataset**
-
-The data is provided in its original form without any additional cleaning or transformations. It is organized into 43 columns ranging from such essential details as app names, descriptions, and genres, along with release and version information, user ratings, and asset links. 
-All the data is grouped by the country API and is presented in the corresponding CSV files: `metadata-US.csv`, `metadata-DE.csv`, and `metadata-UA.csv`.
-
-**Release Notes Dataset**
-
-This dataset is a combined and refined subset of a metadata dataset. The main idea behind its creation is to separate the release notes text of the macOS apps for further analysis.
-
- Key fields related to release notes were selected, and entries were additionally classified by language using the [langdetect](https://pypi.org/project/langdetect/) library. The relevant fields include the app name, release date, current version release date, language, and the release notes themselves. The dataset primarily focuses on the release notes texts, so was additionally deduplicated by this attribute, resulting in over 24,000 apps.
- The dominant languages are English (75%) and German (13%); the others have less than 600  entries (3%). The data is organized in a single CSV file: `release-notes.csv`.
-
-**Descriptions Dataset** 
-
-By analogy with the Release Notes dataset, we also formed a separate one from the metadata dataset with app descriptions. The corresponding fields were selected, and each record was additionally assigned with the description language detected by the  [langdetect](https://pypi.org/project/langdetect/) library so that the dataset is organized into five columns, including app name, bundle id, id, language, and description text.
-
-In the final step, the descriptions were deduplicated, resulting in almost 39,000 unique records. The prevalent language is English (78%), followed by German (16%); the rest are less than 2%. The data is organized in a single CSV file: `descriptions.csv`.
+<!--For the convenience of further analysis, we present the data as three separate datasets. -->
 
 <!--## Dataset Creation
 
@@ -105,7 +89,14 @@ In the final step, the descriptions were deduplicated, resulting in almost 39,00
 
 <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
 
-[More Information Needed]
+The data was fetched by querying the iTunes Search API with
+the request:
+
+`https://itunes.apple.com/search?term={term} &country={country}&entity={entity}&genreId=genre &limit={limit}&offset={offset}},` 
+
+where the `term` parameter was selected in a way that maximized app types and skipped games; `country` and `offset` had to be specified to avoid the API limitations.
+ 
+The data is provided in its original form without any additional cleaning or transformations. It contains over 87,000 samples and is grouped by the country API and is presented in the corresponding CSV files: `metadata-US.csv`, `metadata-DE.csv`, and `metadata-UA.csv`.
 
 <!--
 #### Who are the source data producers?