心理信息
计算机科学
数字化
自然语言
对偶(语法数字)
数据科学
自然(考古学)
认知科学
自然语言处理
人工智能
心理学
语言学
梅德林
考古
法学
哲学
历史
计算机视觉
政治学
作者
Jonah Berger,Grant Packard
出处
期刊:American Psychologist
[American Psychological Association]
日期:2021-12-16
卷期号:77 (4): 525-537
被引量:65
摘要
Language can provide important insights into people, and culture more generally. Further, the digitization of information has made more and more textual data available. But by itself, all that data are just that: data. Realizing its potential requires turning that data into insight. We suggest that automated text analysis can help. Recent advances have provided novel and increasingly accessible ways to extract insight from text. While some psychologists may be familiar with dictionary methods, fewer may be aware of approaches like topic modeling, word embeddings, and more advanced neural network language models. This article provides an overview of natural language processing and how it can be used to deepen understanding of people and culture. We outline the dual role of language (i.e., reflecting things about producers and impacting audiences), review some useful text analysis methods, and discuss how these approaches can help unlock a range of interesting questions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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