Challenges for computational lexical semantic change

The computational study of lexical semantic change (LSC) has taken off in the past
few years and we are seeing increasing interest in the field, from both
computational sciences and linguistics. Most of the research so far has focused on methods
for modelling and detecting semantic change using large diachronic textual data,
with the majority of the approaches employing neural embeddings. While
methods that offer easy modelling of diachronic text are one of the main reasons for
the spiking interest in LSC, neural models leave many aspects of the problem
unsolved. The field has several open and complex challenges. In this chapter, we aim
to describe the most important of these challenges and outline future directions.