An introductory guide for conducting psychological research with big data.

Abstract

Big Data can bring enormous benefits to psychology. However, many psychological researchers show skepticism in undertaking Big Data research. Psychologists often do not take Big Data into consideration while developing their research projects because they have difficulties imagining how Big Data could help in their specific field of research, imagining themselves as "Big Data scientists," or for lack of specific knowledge. This article provides an introductory guide for conducting Big Data research for psychologists who are considering using this approach and want to have a general idea of its processes. By taking the Knowledge Discovery from Database steps as the fil rouge, we provide useful indications for finding data suitable for psychological investigations, describe how these data can be preprocessed, and list some techniques to analyze them and programming languages (R and Python) through which all these steps can be realized. In doing so, we explain the concepts with the terminology and take examples from psychology. For psychologists, familiarizing with the language of data science is important because it may appear difficult and esoteric at first approach. As Big Data research is often multidisciplinary, this overview helps build a general insight into the research steps and a common language, facilitating collaboration across different fields.