  Live languages continuously evolve to integrate the cultural change of human
societies. This evolution manifests through neologisms (new words) or
\textbf{semantic changes} of words (new meaning to existing words).
Understanding the meaning of words is vital for interpreting texts coming from
different cultures (regionalism or slang), domains (e.g., technical terms), or
periods. In computer science, these words are relevant to computational
linguistics algorithms such as translation, information retrieval, question
answering, etc. Semantic changes can potentially impact the quality of the
outcomes of these algorithms. Therefore, it is important to understand and
characterize these changes formally. The study of this impact is a recent
problem that has attracted the attention of the computational linguistics
community. Several approaches propose methods to detect semantic changes with
good precision, but more effort is needed to characterize how the meaning of
words changes and to reason about how to reduce the impact of semantic change.
This survey provides an understandable overview of existing approaches to the
\textit{characterization of semantic changes} and also formally defines three
classes of characterizations: if the meaning of a word becomes more general or
narrow (change in dimension) if the word is used in a more pejorative or
positive/ameliorated sense (change in orientation), and if there is a trend to
use the word in a, for instance, metaphoric or metonymic context (change in
relation). We summarized the main aspects of the selected publications in a
table and discussed the needs and trends in the research activities on semantic
change characterization.
