How to Identify Hot Topics in Psychology Using Topic Modeling
How to Identify Hot Topics in Psychology Using Topic Modeling
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DOI：
10.1027/2151-2604/a000318
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发表时间：
2018-01-01
影响因子：
1.8
通讯作者：
Fischer, Andreas
中科院分区：
文献类型：
--
作者：
Bittermann, Andre;Fischer, Andreas
心理学出版物中的潜在主题和趋势进行了检查，以确定心理学的热点。主题建模与基于分类的科学计量方法进行了对比，以证明前者的好处。具体而言，分析了PSYNDEX数据库中记录的1980年至2016年德语和英语出版物在德语国家的心理学出版物产出。基于潜在狄利克雷分配（LDA）的主题建模应用于314,573出版物的语料库。主题建模的输入是出版物的受控术语，即心理学关键词的标准化词汇表。根据这些受控术语，确定了500个主题，并确定了趋势主题。这些数据中增长趋势最高的热门话题是神经心理学、在线治疗、跨文化方面、创伤和视觉注意力。总之，研究结果表明，主题可以揭示更详细的研究趋势比标准化分类的见解。这种方法的可能应用，局限性和研究合成的影响进行了讨论。
Latent topics and trends in psychological publications were examined to identify hotspots in psychology. Topic modeling was contrasted with a classification-based scientometric approach in order to demonstrate the benefits of the former. Specifically, the psychological publication output in the German-speaking countries containing German-and English-language publications from 1980 to 2016 documented in the PSYNDEX database was analyzed. Topic modeling based on latent Dirichlet allocation (LDA) was applied to a corpus of 314,573 publications. Input for topic modeling was the controlled terms of the publications, that is, a standardized vocabulary of keywords in psychology. Based on these controlled terms, 500 topics were determined and trending topics were identified. Hot topics, indicated by the highest increasing trends in this data, were facets of neuropsychology, online therapy, cross-cultural aspects, traumatization, and visual attention. In conclusion, the findings indicate that topics can reveal more detailed insights into research trends than standardized classifications. Possible applications of this method, limitations, and implications for research synthesis are discussed.