Racial Identity Claims in the #TrudeauMustGo Data

27 August 2025, Version 1
This content is an early or alternative research output and has not been peer-reviewed at the time of posting.

Abstract

To better understand racial identity claims animating Canadian politics, this paper examines Twitter user activity and bio descriptions from two episodes in the lengthy history of #TrudeauMustGo. The first sample is drawn from 643,669 Tweets gathered between August 29 and October 22, 2019 using the Twitter Search API during the Canadian election campaign. The second sample is drawn from 249,046 Tweets gathered via the commercial data provider Meltwater between June 1, 2024 and March 1, 2025. The results of inductive qualitative and mixed methods research are presented through the lens of a machine-learning (ML) model based on 3.7 million labels applied to political Twitter user bios over five years. The core ML model is a binary: "Promoting Trump" versus "Not Promoting Trump" first developed using Canadian election Twitter data in 2019.

Keywords

annotation
machine-learning
Twitter
ARG
election interference
information warfare
QAnon
Canada
Russia
United States

Supplementary weblinks

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