Unveiling Linguistic Authenticity: Analysis of AAE in Performative Poetry

This research delves into the dynamics of stigma and authenticity in nonstandard dialects, particularly African American English (AAE), within performance poetry. Central to the study is how poets' deliberate integration of AAE features provides a linguistically diverse setting, cultivating community solidarity and reflecting authenticity. Drawing on various sociolinguistic theories including Giles’ (1991) Accommodation Theory, Brown and Levinson's (1978) Politeness Theory, Bell's (1984) Audience Design Theory, Schilling-Estes’ (2002) Speaker Design Theory, Kiesling & Schilling-Estes’ (1998) Footing and Framing Approach, and Labov's (2001) variationist sociolinguistic studies, the research explores how the deliberate incorporation of stigmatized dialectical features promotes linguistic authenticity and cultural solidarity within performative poetry events.Non-standard dialects like AAE often face stigma in mainstream contexts, extending to the speakers themselves, suggesting that identifiable features of non-standard language can symbolize group membership, solidarity, and authenticity. The research suggests an inverse relationship between mainstream stigma and authenticity in poetry contexts, proposing that artists utilize dialect stigma to foster solidarity, resulting in the heightened use of stigmatized features in performances compared to conversational settings. The features of AAE analyzed are habitual be, absence of copula, present tense third person -s absence, possessive -s absence, remote time stressed been, consonant cluster reduction, transposed sk and sp, g-dropping, r-lessness and l-lessness, monophthongization, and mutations for dental fricatives involving /t/, /d/, /f/ or /v/ replacing dental fricatives (Green 2002; Thomas 2010).This investigation acknowledges the negative stigmas associated with AAE and explores how speakers challenge established linguistic norms by employing linguistic diversity in artistic expression. Employing a mixed-methods approach, including a comparative analysis of dialectal features employed in live performances versus interview audio, along with a sentiment analysis using VADER to exploit known racial bias in automated Natural Language Processing (NLP), the study reveals patterns and motivations underlying poets' linguistic selections, aimed at conveying authenticity and fostering solidarity among group members. By examining how poets strategically implement dialectal features, the research contributes insights into the connection between cultural appreciation and stigmatized language in performance settings.