Zusammenfassung
Personal Narratives (PN) - recollections of facts, events, and thoughts from
one's own experience - are often used in everyday conversations. So far, PNs
have mainly been explored for tasks such as valence prediction or emotion
classification (i.e. happy, sad). However, these tasks might overlook more
fine-grained information that could nevertheless prove relevant for
understanding PNs. In this work, we propose a novel task for Narrative
Understanding: Emotion Carrier Recognition (ECR). We argue that automatic
recognition of emotion carriers, the text fragments that carry the emotions of
the narrator (i.e. 'loss of a grandpa', 'high school reunion'), from PNs,
provides a deeper level of emotion analysis needed, for instance, in the mental
healthcare domain. In this work, we explore the task of ECR using a corpus of
PNs manually annotated with emotion carriers and investigate different baseline
models for the task. Furthermore, we propose several evaluation strategies for
the task. Based on the inter-annotator agreement, the task in itself was found
to be complex and subjective for humans. Nevertheless, we discuss evaluation
metrics that could be suitable for applications based on ECR.
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