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

Ellie Bennett, Aleksi Sahala


Abstract
Research into emotions is a developing field within Assyriology, and NLP tools for Akkadian texts offers a new perspective on the data. In this submission, 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 the emotion words in their results lists 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.
Anthology ID:
2023.alp-1.22
Volume:
Proceedings of the Ancient Language Processing Workshop
Month:
September
Year:
2023
Address:
Varna, Bulgaria
Editors:
Adam Anderson, Shai Gordin, Bin Li, Yudong Liu, Marco C. Passarotti
Venues:
ALP | WS
SIG:
Publisher:
INCOMA Ltd., Shoumen, Bulgaria
Note:
Pages:
193–202
Language:
URL:
https://aclanthology.org/2023.alp-1.22
DOI:
Bibkey:
Cite (ACL):
Ellie Bennett and Aleksi Sahala. 2023. Using Word Embeddings for Identifying Emotions Relating to the Body in a Neo-Assyrian Corpus. In Proceedings of the Ancient Language Processing Workshop, pages 193–202, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.
Cite (Informal):
Using Word Embeddings for Identifying Emotions Relating to the Body in a Neo-Assyrian Corpus (Bennett & Sahala, ALP-WS 2023)
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PDF:
https://aclanthology.org/2023.alp-1.22.pdf