Data and Code for Sensitivity Analysis of Semantic Clustering Algorithms on Static Word Embeddings

This dataset supports the article “A Comparative Empirical Evaluation of Semantic Clustering Algorithms on Static Word Embeddings” submitted to the International Journal of Information Management Data Insights.

The dataset includes curated word lists, sensitivity analysis results, and executable code used to assess the robustness of Phase 1 semantic clustering experiments. Pre-trained static embeddings (GloVe and fastText) are not redistributed due to licensing constraints and were loaded via the Gensim API.

The materials enable replication of the reported sensitivity analyses and facilitate further comparative research on semantic clustering robustness.