Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
multi-class-classification
Languages:
English
Size:
1M - 10M
License:
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. | |