We find that pre-trained word embeddings provide significant improvements over untrained embeddings, as do the combination of two auxiliary tasks, news-section prediction and part-of-speech tagging. We model each of these factors in a multi-task GRU network to predict headline popularity. These preferences rely on topical, structural, and lexical factors. Publisher = "Association for Computational Linguistics",Ībstract = "Newspapers need to attract readers with headlines, anticipating their readers preferences.
![headline newspaper headline newspaper](https://i0.wp.com/www.newsheadlines.com.ng/wp-content/uploads/2022/08/Own-goal-helps-Arsenal-win-at-Palace-in-Premier-League.jpg)
HEADLINE NEWSPAPER MODS
Cite (Informal): Predicting News Headline Popularity with Syntactic and Semantic Knowledge Using Multi-Task Learning (Lamprinidis et al., EMNLP 2018) Copy Citation: BibTeX Markdown MODS XML Endnote More options… PDF: Video: = "Predicting News Headline Popularity with Syntactic and Semantic Knowledge Using Multi-Task Learning",īooktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing", Association for Computational Linguistics. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 659–664, Brussels, Belgium. Predicting News Headline Popularity with Syntactic and Semantic Knowledge Using Multi-Task Learning. Anthology ID: D18-1068 Volume: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing Month: October-November Year: 2018 Address: Brussels, Belgium Venue: EMNLP SIG: SIGDAT Publisher: Association for Computational Linguistics Note: Pages: 659–664 Language: URL: DOI: 10.18653/v1/D18-1068 Bibkey: lamprinidis-etal-2018-predicting Cite (ACL): Sotiris Lamprinidis, Daniel Hardt, and Dirk Hovy. Feature analysis reveals structural patterns of headline popularity, including the use of forward-looking deictic expressions and second person pronouns. However, we also find that performance is very similar to that of a simple Logistic Regression model over character n-grams.
![headline newspaper headline newspaper](https://makingheadlinenews.com/wp-content/uploads/2022/06/MAKING-HEADLINE-NEWS--scaled.jpg)
Abstract Newspapers need to attract readers with headlines, anticipating their readers’ preferences.