About OpLaDyn

Welcome to the website of the “Understanding Language and Opinion Dynamics using Big Data” project

In the last few years, Human Society has undergone unprecedented changes, driven by the sudden increase in communicating technological devices that surround us, keeping traces of a large amount of our daily activities. This extremely rapid evolution, which is just starting; is associated with a fast adaptive dynamics that induces changes in our everyday practices and has consequences for the nature of the social relations that we develop.

On the one hand, the ubiquity of communication devices, by allowing us to interact with many more individuals, changes the way in which we interact with each other, for example, by allowing interaction among geographically distant people, or by bringing together very different people, who would not have been able to share a discussion or support a cause before, to converge on a particular action. These changes seem to affect the very notion of social interaction. On the other hand, an increasing number of our common actions leave digital traces that are collected by different kinds of agents such as governments, scientific societies, commercial firm and NGOs, etc.

Using different data sources to understand changes on social behaviour

The fact that the activities of human society can be massively monitored and stored is a new feature in history, and the impact of this fact on our behavior is far from trivial. This rapidly increasing amount of data, called Big Data, leads to the urgent question of its storage, organization, retrieval and control. Data scientists concentrate on the technical aspects of these problems in order to make massive data ready to be used. This project addresses two different questions:

(a) How can relevant information be obtained from these massive data, in order to elaborate explanatory models describing the evolution of different aspects of social ties?

(b) What are the possible ethical consequences of the application of Big Data analyses in the study of self-organized human actions?

We are interested in both, searching for traces of social information in raw data and studying the impact that this new situation has on social behavior. Our aim is to contribute to the construction of an interdisciplinary view of the relation between informational pattern correlations, available in Big Data, and the dynamics of social actions, bridging the social and the natural sciences.

Specifically, we will focus on the study of opinion dynamics and language evolution based on data issued from two very different media, on one hand a historical newspaper (the New York Times) and on the other a new online medium (Twitter).