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We here examine how different perspectives of understanding written discourse, like the reader’s, the writer’s or the text’s point of view, affect the quality of emotion annotations. We conducted a series of annotation experiments on two corpora, a popular movie review corpus and a genre- and domain-balanced corpus of standard English. We found statistical evidence that the writer’s perspective yields superior annotation quality overall. However, the quality one perspective yields compared to the other(s) seems to depend on the domain the utterance originates from. Our data further suggest that the popular movie review data set suffers from an atypical bimodal distribution which may decrease model performance when used as a training resource.

Readers vs. Writers vs. Texts: Coping with Different Perspectives of Text Understanding in Emotion Annotation