Impoverished Language Technology: The Lack of (Social) Class in NLP
Amanda Cercas Curry Zeerak Talat Dirk Hovy
Since Labov's (1964) foundational work on the social stratification of
language, linguistics has dedicated concerted efforts towards understanding the
relationships between socio-demographic factors and language production and
perception. Despite the large body of evidence identifying significant
relationships between socio-demographic factors and language production,
relatively few of these factors have been investigated in the context of NLP
technology. While age and gender are well covered, Labov's initial target,
socio-economic class, is largely absent. We survey the existing Natural
Language Processing (NLP) literature and find that only 20 papers even mention
socio-economic status. However, the majority of those papers do not engage with
class beyond collecting information of annotator-demographics. Given this
research lacuna, we provide a definition of class that can be operationalised
by NLP researchers, and argue for including socio-economic class in future
language technologies.