  Computational approach to politeness is the task of automatically predicting
and generating politeness in text. This is a pivotal task for conversational
analysis, given the ubiquity and challenges of politeness in interactions. The
computational approach to politeness has witnessed great interest from the
conversational analysis community. This article is a compilation of past works
in computational politeness in natural language processing. We view four
milestones in the research so far, viz. supervised and weakly-supervised
feature extraction to identify and induce politeness in a given text,
incorporation of context beyond the target text, study of politeness across
different social factors, and study the relationship between politeness and
various sociolinguistic cues. In this article, we describe the datasets,
approaches, trends, and issues in computational politeness research. We also
discuss representative performance values and provide pointers to future works,
as given in the prior works. In terms of resources to understand the
state-of-the-art, this survey presents several valuable illustrations, most
prominently, a table summarizing the past papers along different dimensions,
such as the types of features, annotation techniques, and datasets used.
