@inproceedings{teodorescu-etal-2023-utterance,
    title = "Utterance Emotion Dynamics in Children`s Poems: Emotional Changes Across Age",
    author = "Teodorescu, Daniela  and
      Fyshe, Alona  and
      Mohammad, Saif",
    editor = "Barnes, Jeremy  and
      De Clercq, Orph{\'e}e  and
      Klinger, Roman",
    booktitle = "Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, {\&} Social Media Analysis",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2023.wassa-1.35/",
    doi = "10.18653/v1/2023.wassa-1.35",
    pages = "401--415",
    abstract = "Emerging psychopathology studies are showing that patterns of changes in emotional state {---} emotion dynamics {---} are associated with overall well-being and mental health. More recently, there has been some work in tracking emotion dynamics through one`s utterances, allowing for data to be collected on a larger scale across time and people. However, several questions about how emotion dynamics change with age, especially in children, and when determined through children`s writing, remain unanswered. In this work, we use both a lexicon and a machine learning based approach to quantify characteristics of emotion dynamics determined from poems written by children of various ages. We show that both approaches point to similar trends: consistent increasing intensities for some emotions (e.g., anger, fear, joy, sadness, arousal, and dominance) with age and a consistent decreasing valence with age. We also find increasing emotional variability, rise rates (i.e., emotional reactivity), and recovery rates (i.e., emotional regulation) with age. These results act as a useful baselines for further research in how patterns of emotions expressed by children change with age, and their association with mental health."
}