Department of Psychology, University of Milano-Bicocca.
Psychol Methods. 2023 Jun;28(3):580-599. doi: 10.1037/met0000513. Epub 2023 Mar 13.
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 , 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. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
大数据可以给心理学带来巨大的好处。然而，许多心理学研究人员对从事大数据研究持怀疑态度。心理学家在开发研究项目时往往没有考虑大数据，因为他们难以想象大数据如何能帮助他们特定的研究领域，难以想象自己是“大数据科学家”，或者是因为缺乏特定的知识。本文为考虑采用这种方法的心理学家提供了一个进行大数据研究的入门指南，让他们对其过程有一个大致的了解。我们以数据库中的知识发现步骤为基础，为寻找适合心理学研究的数据提供了有用的指示，描述了如何对这些数据进行预处理，并列出了一些分析这些数据的技术以及编程语言（R 和 Python），所有这些步骤都可以通过这些语言实现。在这样做的过程中，我们用数据科学的术语解释了概念，并从心理学中举例说明。对于心理学家来说，熟悉数据科学的语言很重要，因为它一开始可能看起来很难和深奥。由于大数据研究通常是多学科的，因此这个概述有助于对研究步骤和通用语言建立一个总体的了解，促进不同领域之间的合作。（PsycInfo 数据库记录（c）2023 APA，保留所有权利）。
