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Helping News Editors Write Better Headlines: A Recommender to Improve the Keyword Contents and Shareability of News Headlines
Date Issued
2016-07-10
Date Available
2016-09-20T10:13:39Z
Abstract
We present a software tool that employs state-of- the-art natural language processing (NLP) and ma- chine learning techniques to help newspaper editors compose effective headlines for online publication. The system identifies the most salient keywords in a news article and ranks them based on both their overall popularity and their direct relevance to the article. The system also uses a supervised regres- sion model to identify headlines that are likely to be widely shared on social media. The user inter- face is designed to simplify and speed the editor’s decision process on the composition of the head- line. As such, the tool provides an efficient way to combine the benefits of automated predictors of engagement and search-engine optimization (SEO) with human judgments of overall headline quality.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Copyright (Published Version)
© 2016 International Joint Conferences on Artificial Intelligence
Web versions
Language
English
Status of Item
Peer reviewed
Journal
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence
Conference Details
Natural Language Processing meets Journalism IJCAI-16 Workshop, New York, United States of America, 10 July 2016
This item is made available under a Creative Commons License
File(s)
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Name
insight_publication.pdf
Size
604.03 KB
Format
Adobe PDF
Checksum (MD5)
38c3a0af22486ae5d63d27cc337a4e79
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