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Codeswitching is the action of switching between languages to better impart information to a recipient. This thesis introduces a set of codeswitching translator tools as a method of disrupting the potentially damaging structures of tribal politics through the manipulation of ideologically specific language norms. We first investigate how tribalism and group identity impact our ability to participate in political discourse. Using this insight from a host of different research disciplines, we design an iterative testing environment for a variety of ‘codeswitching’ translators in order to see the impact of translations ranging in complexity from simple word and syntax substitution through to machine learning back-translation. Though back-translation was not found to be an effective technique, simple substitution methods provided a foundation of effectiveness and proof of concept among test participants, especially those that identified as politically aligned.

Us vs them: Tribalism, selective exposure & how non-partisan online news media engagement can be facilitated