Power and Personal Experience in Online Anonymous Communities: A Corpus-Driven Exploration

Abstract

The paper presents an innovative corpus study on Personal Experience as a pragmatic-discursive resource to express power in anonymous online interactions. Specifically, we explore a corpus-driven methodology to extract lexicogrammatical features typical of Personal Experience in representative samples (around 160,000 words) of 3 online fora. The method is rooted in Part of Speech and semantic domain keyness (Rayson, 2008), which we combine in Corpus Language Queries to extract statistically relevant patterns in the data. Results show that the datasets share a "core" set of key lexico-grammatical features. Furthermore, our findings align with the scientific literature exploring personal experiences and narratives in many different genres. This strongly supports the idea that our inductive protocol can be reliably used to break down the discursive textual function of Personal Experience into lower-level, scalable features. In other words, we suggest that our method can be used to extract "form" (i.e. lexical, grammatical, and syntactical units) from "function" (i.e. pragmatic and discursive annotations). Findings are discussed in the context of language and power in online interactions and in the context of building automatic feature detectors for the analysis of larger cross-genre corpora.