Big data shows people’s collective behaviour follows strong periodic patterns

New research has revealed that by using big data to analyse massive data sets of modern and historical news, social media and Wikipedia page views, periodic patterns in the collective behaviour of the population can be observed that could otherwise go unnoticed. Academics from the University of Bristol's ThinkBIG project , led by Nello Cristianini , Professor of Artificial Intelligence, have published two papers that have analysed periodic patterns in daily media content and consumption: the first investigated historical newspapers, the second Twitter posts and Wikipedia visits. The two sets of findings, taken together, show that people's collective behaviour follows strong periodic patterns and is more predictable than previously thought. However, these patterns can often only be revealed when analysing the activities of a large number of people for a very long time, and until recently this has been a very difficult task. By using big data technologies it is now possible to obtain a unified look at newspaper content, for dozens of newspapers at the same time, spanning several decades or to analyse the contents posted on Twitter by large numbers of users, or even the Wikipedia pages visited. Professor Nello Cristianini, from the Department of Engineering Mathematics , said: "What emerges is a glimpse at the regularities in our behaviour that are hidden behind the day-to-day variations in our lives.