Towards Computing Inferences from English News Headlines

  • Elizabeth Jasmi GeorgeEmail author
  • Radhika Mamidi
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1215)


Newspapers are a popular form of written discourse, read by many people, thanks to the novelty of the information provided by the news content in it. A headline is the most widely read part of any newspaper due to its appearance in a bigger font and sometimes in colour print. In this paper, we suggest and implement a method for computing inferences from English news headlines, excluding the information from the context in which the headlines appear. This method attempts to generate the possible assumptions a reader formulates in mind upon reading a recent headline. The generated inferences could be useful for assessing the impact of the news headline on readers, including children. The understandability of the current state of social affairs depends significantly on the assimilation of the headlines. As the inferences that are independent of the context depend mainly on the syntax of the headline, dependency trees of headlines are used in this approach, to find the syntactic structure of the headlines and to compute inferences out of them. Considering the headline as the entry point to a piece of news and a source rich information about the news, we explored a headline’s potential of giving an idea about the current state of affairs, leveraging the syntax structure.


Computing inferences Presuppositions Conventional implicatures Pragmatics News discourse News headline 



We would like to thank Dr. Monojit Choudhury, Microsoft Research-Bangalore, for suggesting this topic of research as part of the Computational Socio-pragmatics course he taught at IIIT-H. We would also like to thank all the anonymous reviewers for carefully reading through a previous version of this document and for offering valuable suggestions for improvement.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.LTRCInternational Institute of Information Technology, HyderabadHyderabadIndia

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