Simple Models for Word Formation in English Slang

TL;DR

This paper introduces simple, data-driven generative models for slang word formation phenomena in English, achieving state-of-the-art performance and providing insights into linguistic processes relevant to internet language evolution.

Contribution

It presents novel, effective models for slang word formation, combining linguistic knowledge with data-driven methods, and offers new insights into the generative processes of slang words.

Findings

Models achieve state-of-the-art performance on annotated datasets.

Insights into the linguistic processes of slang word formation.

Applicable to understanding language evolution on the internet.

Abstract

We propose generative models for three types of extra-grammatical word formation phenomena abounding in English slang: Blends, Clippings, and Reduplicatives. Adopting a data-driven approach coupled with linguistic knowledge, we propose simple models with state of the art performance on human annotated gold standard datasets. Overall, our models reveal insights into the generative processes of word formation in slang -- insights which are increasingly relevant in the context of the rising prevalence of slang and non-standard varieties on the Internet.