  Though languages can evolve slowly, they can also react strongly to dramatic
world events. By studying the connection between words and events, it is
possible to identify which events change our vocabulary and in what way. In
this work, we tackle the task of creating timelines - records of historical
"turning points", represented by either words or events, to understand the
dynamics of a target word. Our approach identifies these points by leveraging
both static and time-varying word embeddings to measure the influence of words
and events. In addition to quantifying changes, we show how our technique can
help isolate semantic changes. Our qualitative and quantitative evaluations
show that we are able to capture this semantic change and event influence.
