Simple Models for Word Formation in English Slang
This work addresses the challenge of understanding slang word formation, which is increasingly relevant due to the rise of slang on the Internet, but it is incremental as it builds on existing linguistic and computational approaches.
The authors tackled the problem of modeling word formation in English slang, specifically blends, clippings, and reduplicatives, by proposing simple generative models that achieve state-of-the-art performance on human-annotated datasets.
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.