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arxiv 2309.08627 v1 pith:PQY6SLJ6 submitted 2023-09-12 cs.CL cs.IRcs.LG

Evaluating Dynamic Topic Models

classification cs.CL cs.IRcs.LG
keywords dtmstopicmeasuredatadynamicevaluatingevaluationhuman
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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There is a lack of quantitative measures to evaluate the progression of topics through time in dynamic topic models (DTMs). Filling this gap, we propose a novel evaluation measure for DTMs that analyzes the changes in the quality of each topic over time. Additionally, we propose an extension combining topic quality with the model's temporal consistency. We demonstrate the utility of the proposed measure by applying it to synthetic data and data from existing DTMs. We also conducted a human evaluation, which indicates that the proposed measure correlates well with human judgment. Our findings may help in identifying changing topics, evaluating different DTMs, and guiding future research in this area.

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