Towards Computing Inferences from English News Headlines

TL;DR

This paper presents a method to generate inferences from English news headlines by analyzing their syntactic structure, aiming to understand potential reader assumptions independent of context.

Contribution

It introduces a novel approach using dependency trees to compute inferences solely from headline syntax, excluding contextual information.

Findings

Effective inference generation from headlines demonstrated

Dependency tree analysis proves useful for understanding headline implications

Potential applications in assessing news impact on readers

Abstract

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 fresh 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 greatly 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 syntactical structure of the headlines and to compute inferences out of them.