Microblog Hashtag Generation via Encoding Conversation Contexts

Understand

Automatic hashtag annotation plays an important role in content understanding for microblog posts.

• To date, progress made in this field has been restricted to phrase selection from limited candidates, or word-level hashtag discovery using topic models.
• Different from previous work considering hashtags to be inseparable, our work is the first effort to annotate hashtags with a novel sequence generation framework via viewing the hashtag as a short sequence of words.
• Moreover, to address the data sparsity issue in processing short microblog posts, we propose to jointly model the target posts and the conversation contexts initiated by them with bidirectional attention.