Title: Helping News Editors Write Better Headlines: A Recommender to Improve the Keyword Contents & Shareability of News Headlines,
Abstract: We present a software tool that employs state-of-the-art natural language
processing (NLP) and machine 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 regression model to identify headlines that are likely to be
widely shared on social media. The user interface is designed to simplify and
speed the editor's decision process on the composition of the headline. 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.