In this paper, we present the HybridTrim system which uses a machine learning technique to combine linguistic, statistical and positional information to identify topic labels for headlines in a text. We compare our system with the Topiary system which, in contrast, uses a statistical learning approach to finding topic descriptors for headlines. The Topiary system, developed at the University of...

Headlines play a crucial role in attracting audiences’ attention to online artefacts (e.g. news articles, videos, blogs). The ability to carry out an automatic, largescale analysis of headlines is critical to facilitate the selection and prioritisation of a large volume of digital content. In journalism studies news content has been extensively studied using manually annotated news values – fac...

Nowadays mass media plays a crucial role in people’s lives. Online newspapers constitute part of discourse, which makes for extremely important bodies text the purposes research discourse analysis. In news headlines, careful and sensitive use is made linguistic devices order to make headlines unique different, influence readers, create trust newspaper, and, most importantly, invite encourage re...

BACKGROUND Asbestos-linked public health problems were widely reported in Japan, in 2005. The objective is to apply text mining with network analysis to characterize these problems. METHODS Text mining with network analysis of newspaper headlines including the word 'asbestos' published in 1987 and 2005 was conducted. Outcome measures are occurrence of the words and simultaneous occurrence of ...