Document Topic Alignment Metrics for Evaluating Topic Models of Short-Text Public Health Communications on Social Media
Topic models are widely used to analyze public health-related social media short texts, yet their evaluation remains dominated by metrics that focus entirely on generated topics alone. There is a lack of metrics that quantitatively assess whether assigned topics meaningfully represent the corresponding short-text posts. We propose Document-Topic Alignment metrics (DoTA), an assignment-aware evaluation framework comprising metrics that measure semantic alignment between documents (posts) and their assigned topics. We also introduce margin-based and discriminative variants that capture topic assignment confidence and distinguishability. We evaluate DoTA across five topic models on three pub...
| Authors | Wangjiaxuan Xin, Shuhua Yin, Yaorong Ge et al. |
|---|---|
| Primary category | cs.CL |
| Published | 13 September 2026 |
| Last updated at source | 13 September 2026 |
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