Research map / Probabilistic and scientific modeling / Molecules and proteins
Hashtag-Based Sub-Event Discovery Using Mutually Generative LDA in Twitter
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| replace LDA with mutually generative hashtag-topic model (MGe-LDA) | LDA · ER tweets | H-score (lower better): 0.1468 -> 0.0774 | Helped |
| replace LDA with MGe-LDA | LDA · SB tweets | H-score (lower better): 0.1314 -> 0.0813 | Helped |
| replace LDA with MGe-LDA | LDA · SOTU tweets | H-score (lower better): 0.1318 -> 0.0846 | Helped |
| add hashtag graph to MGe-LDA (ablation) | MGe-LDA · ER tweets | H-score (lower better): 0.0774 -> 0.0232 | Helped |
| add hashtag graph to MGe-LDA (ablation) | MGe-LDA · SB tweets | H-score (lower better): 0.0813 -> 0.0364 | Helped |
| add hashtag graph to MGe-LDA (ablation) | MGe-LDA · SOTU tweets | H-score (lower better): 0.0846 -> 0.0124 | Helped |
| replace HGTM (one-way hashtag generation) with MGe-LDA (mutual generation) | HGTM · ER tweets | H-score (lower better): 0.1389 -> 0.0774 | Helped |
| replace tf-idf+SOM with topic-model features (LDA) | tf-idf+SOM · ER tweets | H-score (lower better): 0.9604 -> 0.1468 | Helped |
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