South Korean Workplace Bullying Q&A Posts for Topic Modeling, 2019-2025

10,788 workplace-bullying-related question posts were collected from Naver Knowledge iN between July 16, 2019 and July 31, 2025. The dataset, created by Hyunjoo Oh and last updated in May 2026, contains Korean text preprocessed for Latent Dirichlet Allocation (LDA) topic modeling, resulting in 12-topic and 4-topic solutions.

Use Cases

• Analyze discourse themes like hierarchical conflict and institutional responses based on the described topic modeling results.
• Study temporal shifts in discussion topics, such as the increased focus on reporting and legal advice, based on the described period comparisons.
• Train or benchmark topic models for Korean social Q&A text based on the preprocessed corpus of 10,788 posts.

Strengths

• 10,788 text posts provide a substantial corpus for analysis.
• Clear temporal coverage from July 2019 to July 2025 allows for longitudinal study.
• Topic modeling results, including a selected 12-topic solution, are described in the metadata.

Limitations

• Row count for the underlying data is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small in file size (677.9 KB), indicating limited raw data scope.

Provenance

Source

Naver Knowledge iN (South Korea)

Collection Method

Question posts were collected, deduplicated, filtered, and preprocessed for LDA topic modeling.

Time Range

July 16, 2019 to July 31, 2025

Freshness

Last updated 2026-05-05 05:28:48; freshness should be verified.

Geography

South Korea