Exploring scientific trajectories of a large-scale dataset using topic-integrated path extraction

Highlights：

• Main path analysis (MPA) is the most widely accepted approach to tracing knowledge transfer in a research field. In this study, we extracted multiple longest paths from the multidisciplinary academic field's citation network and integrating topic modeling to the extracted paths.

• We considered three main aspects of trajectory analysis when analyzing the represented documents through the extracted paths: emergence, authority, and topic dynamics.

• We claimed that a small-scale dataset results in main paths with relatively short lengths of paths. We exploited the longest path algorithm, which searches paths exhaustively, enabling the identification of more sequences of knowledge transfer in the large-scale datasets.

• This study revealed the knowledge development tracks of topics in the healthcare informatics field. Topic-integrated longest paths highlight important topics that move from the main path to extended subfields.