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Development of a user-friendly app for exploring and analyzing research topics in psychology

Background Keeping track of the developments in a scientific field can be challenging. Regarding increasing numbers of publications, summarizing the contents of hundreds of thousands of scientific publications on specific topics is necessary to gain insights into the processes of a scientific field. Many databases offer classifications, i.e., broad subject headings for categorizing the publications’ contents. Past research has treated these categories as research topics (e.g., Krampen, 2016), but regarding the level of detail, topicality, and flexibility this approach has been criticized (e.g., Bittermann & Fischer, 2018). Techniques for automated content analysis represent a promising approach for getting insight into large text corpora. Topic modeling (e.g., Blei, Ng, & Jordan, 2003), in particular, is gaining in popularity in scientometrics. In their well-known paper, Griffiths and Steyvers (2004) demonstrated how to find scientific topics by applying topic models to a corpus of scientific abstracts. A topic-guided and user-friendly interface for databases of scientific literature can open publication trends to a broader audience with various user scenarios: exploring the current “hot topics,” investigating the ups and downs of topic popularity over time, or comparing publication trends concerning societal processes (e.g., the increasing trend of a topic referring to refugees and emotional trauma in psychological publications from the German-speaking countries after 2015).