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This repository implements a pipeline to store various data of files from a large unstructured dataset. These fields are used for topic modeling (wordclouds, based on low-dimensional versions of ...

Abstract: We propose a novel multimodal topic modeling framework to extract and explain latent themes in extensive collections of digitized artworks. Our approach leverages CLIP's contrastive ...

An efficient analysis pipeline, integrating topic modeling with large language model (LLM) summarizing and human verification, was applied to identify the discussion topics. Results: We analyzed 1765 ...

Abstract: Topic modeling is a crucial technique for extracting latent themes from unstructured text data, particularly valuable in analyzing survey responses. However, traditional methods often only ...

Results: Coherence scores indicated an optimal topic solution of k=40 (coherence=0.58) for English and k=30 (coherence=0.52) for Spanish. Thematically, we observed similar content in both languages, ...