Workplace Bullying Discourse Topic Models from South Korean Q&A Posts, 2019-2025

Hyunjoo Oh published a dataset of 10,788 workplace-bullying-related question posts collected from Naver Knowledge iN between July 16, 2019 and July 31, 2025. The text data was preprocessed and analyzed using Latent Dirichlet Allocation (LDA) topic modeling, resulting in a 12-topic solution for the full corpus and a 4-topic summary of macro-level discourse frames. The dataset is available under a CC-BY-4.0 license and was last updated on May 5, 2026.

Use Cases

• Analyzing shifts in public discourse themes around workplace bullying based on the described hierarchical/relational conflict and institutional response topics.
• Training topic models for social science research using a corpus of preprocessed Korean help-seeking narratives.
• Studying the co-occurrence of psychosocial distress and procedural concerns in online discourse following new legislation.

Strengths

• Contains 10,788 text entries specifically related to workplace bullying.
• Covers a defined time period from July 16, 2019 to July 31, 2025, allowing for longitudinal analysis.
• Topic modeling results (12-topic and 4-topic solutions) are provided and were evaluated using coherence and perplexity metrics.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the processed topic model data is unknown, which may limit suitability assessment.
• The data source is limited to a single South Korean Q&A platform, which may introduce source bias.

Provenance

Source

Hyunjoo Oh via figshare

Collection Method

Question posts were collected from Naver Knowledge iN, deduplicated, filtered, and preprocessed before LDA topic modeling was applied.

Time Range

July 16, 2019 to July 31, 2025

Freshness

Last updated 2026-05-05 05:28:49; freshness should be verified.

Geography

South Korea