@article{ito-etal-2026-naist,
    title = "{NAIST} {LIFE} {STORY}: A Seven-Year Crowdsourced Dataset of {J}apanese Emotion-related Episodes",
    author = "Ito, Kazuhiro  and
      Hayashi, Junko  and
      Nagai, Hiroyuki  and
      Wakamiya, Shoko  and
      ARAMAKI, Eiji",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    journal = "International Conference on Language Resources and Evaluation",
    volume = "main",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://preview.aclanthology.org/ingest-lrec/2026.lrec-main.522/",
    pages = "6573--6584",
    abstract = "Existing emotion datasets have supported a wide range of NLP tasks, but most are static resources that capture language use only at the time of their creation. As a result, they cannot represent how emotional meanings shift in response to cultural and social change. To address this limitation, we present NAIST LIFE STORY, a seven-year collection of Japanese emotion-related episodes that reflect contemporary topics across multiple years. Since 2017, 1,000 crowdsourced participants per quarter have written short texts describing personal experiences associated with seven emotions: anger, anxiety, disgust, trust, joy, sadness, and surprise. The dataset currently spans 28 periods and includes gender and age information for each participant. Analyses reveal systematic differences in text length and lexical diversity across emotions, as well as clear temporal trends linked to major events such as the COVID-19 pandemic. A preliminary experiment with a large language model shows that using this dataset as contextual evidence improves time-aware emotion inference, demonstrating its value for studying the evolving relationship between emotion and language."
}