Temporal Language Analysis in News Media and Social Networks

Abstract

The amount of text we can find on the Internet is constantly growing, what makes not feasible to manually analyse such as quantity of information. The Natural Language Processing (NLP) research field has provided a set of tools and techniques that allow human beings to extract relevant data from unstructured pieces of text that come from electronic sources such as digital newspapers or online social networks. The aim of this article is to make a temporal analysis of both formal (newspaper articles) and informal (Twitter messages) texts sources. In this article, we will analyse how some terms evolve in time and the correlation between the formal and informal corpora.