Academy & Industry Research Collaboration Center (AIRCC)

Volume 10, Number 14, November 2020

A Pattern-Mining Driven Study on Differences of Newspapers in expressing Temporal Information


Yingxue Fu1, 2 and Elaine Uí Dhonnchadha2, 1University of St Andrews, UK, 2Trinity College Dublin, Ireland


This paper studies the differences between different types of newspapers in expressing temporal information, which is a topic that has not received much attention. Techniques from the fields of temporal processing and pattern mining are employed to investigate this topic. First, a corpus annotated with temporal information is created by the author. Then, sequences of temporal information tags mixed with part-of-speech tags are extracted from the corpus. The TKS algorithm is used to mine skip-gram patterns from the sequences. With these patterns, the signatures of the four newspapers are obtained. In order to make the signatures uniquely characterize the newspapers, we revise the signatures by removing reference patterns. Through examining the number of patterns in the signatures and revised signatures, the proportion of patterns containing temporal information tags and the specific patterns containing temporal information tags, it is found that newspapers differ in ways of expressing temporal information.


Pattern Mining, TKS algorithm, Temporal Annotation, Tabloids and Broadsheets.