Since 2020, the language surrounding transgender women in American media outlets has become increasingly vitriolic through the misrecognition and subsequent projection of a threatening transfemininity. While violence against trans women is unfortunately nothing new, transmisogyny has only relatively recently become a viral phenomenon in mainstream news outlets. Alarmingly, the recent rise in transmisogynistic rhetoric in the news coincides with a resurgence of reactionary populism and the mainstreaming of conspiratorial rhetoric. As organized transphobia increasingly relies on the discursive myth of a “silent majority” to provide cover for its political program, transgender women have become the latest bogeymen for the far-right. This current wave of organized transphobia includes language pulled from anti-semitic conspiracy theories slightly shifted for a new scapegoat. My project implements a textual coding schema via which to analyze the news, in order to create a map of the conspiratorial rhetoric underpinning [this new media landscape of transmisogyny. Using MAXQDA, I will analyze aggregated news articles using discursive and sentiment analysis. This project will address language and linguistic forms only, pulling sample articles discussing transgender issues from popular news sites in the United States, identifying common tropes, including: transgressing the mainstream, the creation of recency, appeal to reason, the weaponization of children , anecdotal language, and moral appeals to tradition. Following this period of qualitative coding, I will build a conclusive rubric on how to recognize organized transmisogyny, hosting an interactive map of the compiled data online.

---