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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 ...

1 AI Meteorological Research Division, National Institute of Meteorological Sciences, Jeju, Republic of Korea 2 Artificial Intelligence Meteorological Technology Research Society, Korea Meteorological ...

For topic modeling, posts with <50 tokens were removed, leaving 53.81% (4059/7543) of the posts, which were analyzed using latent Dirichlet allocation with coherence score optimization to identify the ...

CERM and Department of Chemistry “Ugo Schiff”, University of Florence, Via Luigi Sacconi 6, Sesto Fiorentino 50019, Italy Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine, Via ...

We used multiple topic mining approaches, such as latent Dirichlet allocation, nonnegative matrix factorization, and word-embedding methods. Sentiment analysis used TextBlob and Valence Aware ...