Tomek Strzalkowski author Anna Newheiser author Nathan Kemper author Ning Sa author Bharvee Acharya author Gregorios Katsios author 2020-jul text Association for Computational Linguistics Online conference publication In this paper we describe computational ethnography study to demonstrate how machine learning techniques can be utilized to exploit bias resident in language data produced by communities with online presence. Specifically, we leverage the use of figurative language (i.e., the choice of metaphors) in online text (e.g., news media, blogs) produced by distinct communities to obtain models of community worldviews that can be shown to be distinctly biased and thus different from other communities’ models. We automatically construct metaphor-based community models for two distinct scenarios: gun rights and marriage equality. We then conduct a series of experiments to validate the hypothesis that the metaphors found in each community’s online language convey the bias in the community’s worldview. strzalkowski-etal-2020-generating https://www.aclweb.org/anthology/2020.figlang-1.23 2020-jul 165 175