当前位置: X-MOL 学术Psychological Methods › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
An introductory guide for conducting psychological research with big data.
Psychological Methods ( IF 10.929 ) Pub Date : 2023-03-13 , DOI: 10.1037/met0000513
Michela Vezzoli 1 , Cristina Zogmaister 1
Affiliation  

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. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

中文翻译:

利用大数据进行心理学研究的入门指南。

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进行大数据研究表示怀疑。心理学家在开发研究项目时通常不会考虑大数据,因为他们很难想象大数据如何在他们的特定研究领域提供帮助,将自己想象为“大数据科学家”,或者缺乏特定知识。本文为正在考虑使用这种方法并希望对其过程有一个总体了解的心理学家提供了进行大数据研究的介绍性指南。通过以数据库中的知识发现步骤为基础,我们为寻找适合心理调查的数据提供了有用的指示,描述了如何预处理这些数据,并列出了一些分析它们的技术以及可以实现所有这些步骤的编程语言(R 和 Python)。在此过程中,我们用术语解释这些概念,并以心理学为例。对于心理学家来说,熟悉数据科学的语言很重要,因为乍一看它可能显得困难且深奥。由于大数据研究通常是多学科的,因此这种概述有助于建立对研究步骤和共同语言的一般见解,从而促进不同领域的协作。(PsycInfo 数据库记录 (c) 2023 APA,保留所有权利)。熟悉数据科学的语言很重要,因为乍一看它可能显得困难且深奥。由于大数据研究通常是多学科的,因此这种概述有助于建立对研究步骤和共同语言的一般见解,从而促进不同领域的协作。(PsycInfo 数据库记录 (c) 2023 APA,保留所有权利)。熟悉数据科学的语言很重要,因为乍一看它可能显得困难且深奥。由于大数据研究通常是多学科的,因此这种概述有助于建立对研究步骤和共同语言的一般见解,从而促进不同领域的协作。(PsycInfo 数据库记录 (c) 2023 APA,保留所有权利)。
更新日期:2023-03-13
down
wechat
bug