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README.md

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 ---
-license: apache-2.0
+annotations_creators:
+- machine-generated
+language:
+- en
+language_creators:
+- found
+license:
+- apache-2.0
+multilinguality:
+- monolingual
+pretty_name: stackoverflow_post_questions
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+tags:
+- stackoverflow
+- technical questions
+task_categories:
+- text-classification
+task_ids:
+- multi-class-classification
 ---
+
+# Dataset Card for [Stackoverflow Post Questions]
+
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Source Data](#source-data)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+Companies that sell Open-source software tools usually hire an army of Customer representatives to try to answer every question asked about their tool. The first step in this process 
+is the prioritization of the question. The classification scale usually consists of 4 values, P0, P1, P2, and P3, with different meanings across every participant in the industry. On 
+the other hand, every software developer in the world has dealt with Stack Overflow (SO); the amount of shared knowledge there is incomparable to any other website. Questions in SO are 
+usually annotated and curated by thousands of people, providing metadata about the quality of the question. This dataset aims to provide an accurate prioritization for programming 
+questions.
+
+
+### Dataset Summary
+
+The dataset contains the title and body of stackoverflow questions and a label value(0,1,2,3) that was calculated using thresholds defined by SO badges.
+
+### Languages
+
+English
+
+## Dataset Structure
+
+title: string,
+body: string,
+label: int
+
+### Data Splits
+
+The split is 40/40/20, where classes have been balaned to be around the same size.
+
+## Dataset Creation
+
+The data set was extracted and labeled with the following query in BigQuery:
+
+```
+SELECT
+  title,
+  body,
+  CASE
+    WHEN score >= 100 OR favorite_count >= 100 OR view_count >= 10000 THEN 0
+    WHEN score >= 25 OR favorite_count >= 25 OR view_count >= 2500  THEN 1
+    WHEN score >= 10 OR favorite_count >= 10 OR view_count >= 1000 THEN 2
+    ELSE 3
+  END AS label
+FROM `bigquery-public-data`.stackoverflow.posts_questions
+```
+
+### Source Data
+
+The data was extracted from the Big Query public dataset: `bigquery-public-data.stackoverflow.posts_questions`
+
+#### Initial Data Collection and Normalization
+
+The original dataset contained high class imbalance:
+
+label	count
+0	977424
+1	2401534
+2	3418179
+3	16222990
+Grand Total	23020127
+
+The data was sampled from each class to have around the same amount of records on every class.
+
+### Contributions
+
+Thanks to [@pacofvf](https://github.com/pacofvf) for adding this dataset.

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