Microblog Hashtag Generation via Encoding Conversation Contexts
Table 6: F1@1 scores (%) for our variants.
['[BOLD] Model', '[BOLD] Twitter', '[BOLD] Weibo']
Ablation Study. To this end, our model is compared with its five variants below: Seq2Seq (post only), Seq2Seq (conv only), and Seq2Seq (post+conv), using standard seq2seq to generate hashtags from their target posts, conversation contexts, and their concatenation, respectively; Our model (post-att only) and Our model (conv-att only), whose decoder only takes vp and vc defined in Eq. The results show that solely encoding target posts is more effective than modeling the conversations alone, but exploring their joint effects can further boost the performance, especially combined with a bi-attention mechanism over them.