Open AccessPosted Content
Helping News Editors Write Better Headlines: A Recommender to Improve the Keyword Contents & Shareability of News Headlines
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TLDR
In this article, the authors present a software tool that employs state-of-the-art NLP and machine learning techniques to help newspaper editors compose effective headlines for online publication.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.read more
Citations
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Proceedings ArticleDOI
[Un]breaking News: Design Opportunities for Enhancing Collaboration in Scientific Media Production
TL;DR: This work asks the research question: what pain points in scientific media production afford opportunities for future HCI innovation?
Proceedings ArticleDOI
Automatic Extraction of News Values from Headline Text
TL;DR: This paper presents the first attempt at a fully automatic extraction of news values from headline text, applied on a large headlines corpus collected from The Guardian, and evaluated by comparing it with a manually annotated gold standard.
Posted Content
Attractive or Faithful? Popularity-Reinforced Learning for Inspired Headline Generation.
TL;DR: This paper generates inspired headlines that preserve the nature of news articles and catch the eye of the reader simultaneously through a novel framework called POpularity-Reinforced Learning for inspired Headline Generation (PORL-HG).
Journal ArticleDOI
Attractive or Faithful? Popularity-Reinforced Learning for Inspired Headline Generation
TL;DR: Zhang et al. as discussed by the authors proposed a novel framework called POpularity-Reinforced Learning for inspired Headline Generation (PORL-HG), which exploits the extractive-abstractive architecture with Popular Topic Attention (PTA) for guiding the extractor to select the attractive sentence from the article and a popularity predictor to guide the abstractor to rewrite the sentence.
Proceedings ArticleDOI
Learning to Determine the Quality of News Headlines.
TL;DR: This paper proposes four indicators to determine the quality of published news headlines based on their click count and dwell time, which are obtained by website log analysis and uses soft target distribution of the calculated quality indicators to train the proposed deep learning model, which outperforms other state-of-the-art NLP models.
References
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Proceedings ArticleDOI
The Stanford CoreNLP Natural Language Processing Toolkit
Christopher D. Manning,Mihai Surdeanu,John Bauer,Jenny Rose Finkel,Steven Bethard,David McClosky +5 more
TL;DR: The design and use of the Stanford CoreNLP toolkit is described, an extensible pipeline that provides core natural language analysis, and it is suggested that this follows from a simple, approachable design, straightforward interfaces, the inclusion of robust and good quality analysis components, and not requiring use of a large amount of associated baggage.
Book
Automatic Summarization
TL;DR: The challenges that remain open, in particular the need for language generation and deeper semantic understanding of language that would be necessary for future advances in the field are discussed.
Journal ArticleDOI
Newspaper headlines and relevance: Ad hoc concepts in ad hoc contexts
TL;DR: In this article, the issue of newspaper-headline interpretation is addressed by questioning standard assumptions on how headlines are designed on the basis of largely prescriptive pragmatic guidelines or norms.
Book
The Language of the News
TL;DR: In this paper, the development of newspaper language and its development in a contemporary newspaper language is discussed. But the focus is on the content and structure of news articles rather than the content itself.
BBN/UMD at DUC-2004: Topiary
TL;DR: It is shown that the combination of linguistically motivated sentence compression with statistically selected topic terms performs better than either alone or either alone, according to some automatic summary evaluation measures.