If there's a Trigger Warning, then where's the Trigger? Investigating
  Trigger Warnings at the Passage Level
Matti Wiegmann Jennifer Rakete Magdalena Wolska Benno Stein Martin Potthast
Trigger warnings are labels that preface documents with sensitive content if
this content could be perceived as harmful by certain groups of readers. Since
warnings about a document intuitively need to be shown before reading it,
authors usually assign trigger warnings at the document level. What parts of
their writing prompted them to assign a warning, however, remains unclear. We
investigate for the first time the feasibility of identifying the triggering
passages of a document, both manually and computationally. We create a dataset
of 4,135 English passages, each annotated with one of eight common trigger
warnings. In a large-scale evaluation, we then systematically evaluate the
effectiveness of fine-tuned and few-shot classifiers, and their
generalizability. We find that trigger annotation belongs to the group of
subjective annotation tasks in NLP, and that automatic trigger classification
remains challenging but feasible.