Purpose:

This paper presents an investigation of the concept of “time as aboutness” in various texts, including news articles, social media posts and historical documents. The purpose of this paper is to analyse different forms of temporal information and map the techniques used to extract and categorise this information.

Design/methodology/approach:

A scoping review method was adopted to analyse the chosen literature set. This approach allowed for an overview of the different text document types, the techniques used and their temporal information.

Findings:

The findings reveal six temporal types of time-related data analysis: social events, socio-political events, news events, temporal expressions, historical events and time periods. Studies analysing social media, news articles, Wikipedia entries and historical documents provide insights into event detection and categorisation. In these documents, time appears as sequences of events, temporal expressions or distinct periods. In news articles, time appears as a series of occurrences, while temporal expressions reveal how time is linguistically articulated and perceived. The analysis also covers event categorisation methods, emphasising machine learning techniques, natural language processing, large language models and rule-based systems.

Originality/value:

The analysis of different types of time and methods of extracting temporal information from various texts contributes original insights to the understanding of temporal information. The findings reveal a need for expanding document variety, particularly to include fiction literature and point to the potential use of language models for future temporal information categorisation.