Word Network Topic Model: A Simple but General Solution for Short and Imbalanced Texts
(b) Label counts for news content
['Label Finance', 'Count 133480', 'Label Car', 'Count 18675']
The average number of token in news titles is 5.5. The average number of token in each report is 175.9. Fig. For example, LDA confuses “House” with “Sports”, “Finance” and “Lady”, where “House” and “Finance” may be hard to distinguish because they are strongly relevant, while obviously “House” has few connections with “Sports” and “Lady”. Consequently, LDA almost misclassifies all documents under label “House”. The similar situation also happens to “Culture” and “Health”. However, as shown in Fig. It indicates that WNTM gains outstanding improvement on the performance of identifying rare labels, which evidently justifies the conjecture that WNTM can identify more rare topics than LDA as the text is imbalanced.