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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:
- xml
- Published as:
- Conference proceeding
- Status:
- Published
- Last Updated:
- 2 months ago
- License:
- Attribution
alp-bennett-sahala.pdf