It wasn’t so long ago that topic modelling was all the rage, particularly in the digital humanities. Techniques like Latent Dirichlet Allocation (LDA), which can be used to unveil the hidden thematic structures within documents, extended the possibilities of distant reading—rather than manually coding themes or relying solely on close reading (which brings limits in scale), scholars could now infer latent topics from large corpora.
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Is topic modelling obsolete?
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It wasn’t so long ago that topic modelling was all the rage, particularly in the digital humanities. Techniques like Latent Dirichlet Allocation (LDA), which can be used to unveil the hidden thematic structures within documents, extended the possibilities of distant reading—rather than manually coding themes or relying solely on close reading (which brings limits in scale), scholars could now infer latent topics from large corpora.