• Using Word Embeddings for Identifying Emotions Relating to the Body in a Neo-Assyrian Corpus

    Author(s):
    Ellie Bennett (see profile) , Aleksi Sahala
    Date:
    2023
    Group(s):
    Ancient Near East, Assyriologists, Digital Humanists, History, NLP for Ancient languages
    Subject(s):
    History, Ancient, Mesopotamia, Emotions, Natural language processing (Computer science)
    Item Type:
    Conference proceeding
    Conf. Title:
    Ancient Language Processing Workshop
    Conf. Org.:
    Associated with The 14th International Conference on Recent Advances in Natural Language Processing RANLP 2023
    Conf. Loc.:
    Varna
    Conf. Date:
    8th September 2023
    Tag(s):
    embodied emotions, embodiment, history of emotions, Neo-Assyria, word embeddings
    Permanent URL:
    https://doi.org/10.17613/311m-4117
    Abstract:
    Research into emotions is a developing field within Assyriology, and NLP tools for Akkadian texts offers new perspectives on the data. We use PMI-based word embeddings to explore the relationship between parts of the body and emotions. Using data downloaded from Oracc, we ask which parts of the body were semantically linked to emotions. We do this through examining which of the top 10 results for a body part could be used to express emotions. After identifying two words for the body that have the most emotion words in their results list (libbu and kabattu), we then examine whether those emotion words were indeed used in this manner in the Neo-Assyrian textual corpus. The results indicate that of the two body parts, kabattu was semantically linked to happiness and joy, and had a secondary emotional field of anger.
    Notes:
    ISBN 978-954-452-087-8 https://doi.org/10.26615/978-954-452-087-8.2023_022
    Metadata:
    Published as:
    Conference proceeding    
    Status:
    Published
    Last Updated:
    5 months ago
    License:
    Attribution

    Downloads

    Item Name: pdf alp-bennett-sahala.pdf
      Download View in browser
    Activity: Downloads: 99