Stack Overflow question and tag dataset from Kaggle and BigQuery

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Evidence · 1 claim (1 for) · 1 study (1 design), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

A large dataset of Stack Overflow questions, code snippets, tags, and related metadata assembled from Kaggle and BigQuery for training and evaluating question-tag recommendation systems.

Components

Claims

• BERT-CBA outperformed baseline tag recommendation methods on Precision@K, Recall@K, and F1@K under cross-validation [+M]

Related Products and Programmes

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Key Sources

• Olatinwo, S. O., & Demmans Epp, C. (2025). Predicting Tags for Learner Questions on Stack Overflow. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-024-00441-x

Page metadata

Field	Value
type	product
id	stack-overflow-question-and-tag-dataset-from-kaggle-and-bigquery
title	Stack Overflow question and tag dataset from Kaggle and BigQuery
description	A large dataset of Stack Overflow questions, code snippets, tags, and related metadata assembled from Kaggle and BigQuery for training and evaluating question-tag recommendation systems.
status	review
product_kind	dataset
generated	by process:settle-candidates on 2026-10-28
trust	unverified — no one has confirmed this page's content

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