  The amount of scholarly data has been increasing dramatically over the last
years. For newcomers to a particular science domain (e.g., IR, physics, NLP) it
is often difficult to spot larger trends and to position the latest research in
the context of prior scientific achievements and breakthroughs. Similarly,
researchers in the history of science are interested in tools that allow them
to analyze and visualize changes in particular scientific domains. Temporal
summarization and related methods should be then useful for making sense of
large volumes of scientific discourse data aggregated over time. We demonstrate
a novel approach to analyze the collections of research papers published over
longer time periods to provide a high-level overview of important semantic
changes that occurred over the progress of time. Our approach is based on
comparing word semantic representations over time and aims to support users in
a better understanding of large domain-focused archives of scholarly
publications. As an example dataset we use the ACL Anthology Reference Corpus
that spans from 1979 to 2015 and contains 22,878 scholarly articles.
