A Computational Approach to Politeness with Application to Social Factors

Understand

We propose a computational framework for identifying linguistic aspects of politeness.

• Our starting point is a new corpus of requests annotated for politeness, which we use to evaluate aspects of politeness theory and to uncover new interactions between politeness markers and context.
• These findings guide our construction of a classifier with domain-independent lexical and syntactic features operationalizing key components of politeness theory, such as indirection, deference, impersonalization and modality.
• Our classifier achieves close to human performance and is effective across domains.