  Robotic process automation (RPA) is a software technology that in recent
years has gained a lot of attention and popularity. By now, research on RPA has
spread into multiple research streams. This study aims to create a science map
of RPA and its aspects by revealing latent topics related to RPA, their
research interest, impact, and time development. We provide a systematic
framework that is helpful to develop further research into this technology. By
using an unsupervised machine learning method based on Latent Dirichlet
Allocation, we were able to analyse over 2000 paper abstracts. Among these, we
found 100 distinct study topics, 15 of which have been included in the science
map we provide.
