This repository contains the codebase used in the Digital Humanities Master’s thesis by Ka Yee Suvini Lai. It combines machine learning methods for: Emotion classification using RoBERTa (Sam Lowe's ...
Abstract: As a rich source of direct user needs, online reviews can be effectively analyzed through topic modeling to uncover user preferences and requirements. However, the short and unstructured ...
ABSTRACT: Modeling topics in short texts presents significant challenges due to feature sparsity, particularly when analyzing content generated by large-scale online users. This sparsity can ...
Modeling topics in short texts presents significant challenges due to feature sparsity, particularly when analyzing content generated by large-scale online users. This sparsity can substantially ...
Topic modeling is a technique to uncover the underlying thematic structure in large text corpora. Traditional topic modeling methods, such as Latent Dirichlet Allocation (LDA), have limitations in ...
Researchers from Mount Sinai Health System in New York set out to get an idea of the “hot” and “cold” topics in spine research over time. Their work, “Natural language processing reveals research ...
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