A Computational Framework for Modelling Organisation-Level Semantic Identity from Longitudinal Textual Data

arXiv:2609.29584 · cs.LG, cs.CL · Submitted 2026-08-27 · Read on arXiv

cs.LG, cs.CL

Submitted: 2026-08-27

Updated: 2026-08-27

Terminology

• Embeddings — 35× in this paper · explained in 2 episodes
• Robustness — 30× in this paper · explained in 5 episodes
• Representation Learning — 23× in this paper · explained in 2 episodes
• Adaptation — 18× in this paper · explained in 1 episode
• Aggregation — 14× in this paper · explained in 1 episode
• Semantic Drift — 13× in this paper · explained in 3 episodes
• Accuracy — 9× in this paper · explained in 1 episode
• Abstraction — 6× in this paper · explained in 1 episode
• Interpretability — 6× in this paper · explained in 15 episodes
• Transformer — 6× in this paper · explained in 2 episodes
• Semantic Similarity — 5× in this paper · explained in 2 episodes
• Pairwise Comparisons — 4× in this paper · explained in 2 episodes
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Graph Construction — 3× in this paper · explained in 3 episodes
• Transferability — 3× in this paper · explained in 4 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Empirical Methods in Natural Language Processing — 2× in this paper
• Latent Representation — 2× in this paper · explained in 2 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Semantic Trajectories — 2× in this paper · explained in 2 episodes
• Transformer Models — 2× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Diffusion Processes — 1× in this paper · explained in 2 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Explainability — 1× in this paper · explained in 3 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Probabilistic Forecasting — 1× in this paper · explained in 3 episodes
• Provenance — 1× in this paper · explained in 3 episodes
• Steering — 1× in this paper · explained in 2 episodes

Sources

• Top2Vec: Distributed Representations of Topics
• BERTopic: Neural topic modeling with a class-based TF-IDF procedure
• Semantic Communities and Boundary-Spanning Lyrics in K-pop: A Graph-Based Unsupervised Analysis
• Efficient Estimation of Word Representations in Vector Space

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