PoKi: A Large Dataset of Poems by Children

By Will E. Hipson, Saif M. Mohammad. 2020

7 citations recorded by the source corpus.

Child language studies are crucial in improving our understanding of child well-being; especially in determining the factors that impact happiness, the sources of anxiety, techniques of emotion regulation, and the mechanisms to cope with stress. However, much of this research is stymied by the lack of availability of large child-written texts. We present a new corpus of child-written text, PoKi, which includes about 62 thousand poems written by children from grades 1 to 12. PoKi is especially useful in studying child language because it comes with information about the age of the child authors (their grade). We analyze the words in PoKi along several emotion dimensions (valence, arousal, dominance) and discrete emotions (anger, fear, sadness, joy). We use non-parametric regressions to model developmental differences from early childhood to late-adolescence. Results show decreases in valence that are especially pronounced during mid-adolescence, while arousal and dominance peaked during adolescence. Gender differences in the developmental trajectory of emotions are also observed. Our results support and extend the current state of emotion development research.

Subfields: Natural Language Processing, Evaluation & Benchmarks

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Natural Language Processing

In Evaluation & Benchmarks

Citations in the corpus

LongForm: Effective Instruction Tuning with Reverse Instructions (2023, positive): “From NIv2, we include a selection of ten tasks including poem generation (Hipson and Mohammad, 2020), table to text generation (Iyyer et al., 2017), story generation (Sap et al., 2020; Orbach and Goldberg, 2020; Lin et al., 2019), summarization (Fabbri et al., 2019; Kornilova and Eidelman, 2019;…”