IPHS 300: Artificial Intelligence for the Humanities: Text, Image, and Sound
Document Type
Poster
Publication Date
Fall 2019
Abstract
For my final project in AI for the Humanities, I knew that I wanted to examine the creative role of translators in classic literature. I ran three different translations of Homer’s The Odyssey through Syuzhet.R, a sentiment analysis tool that has grown increasingly popular in the Digital Humanities field. Syuzhet tracks the emotional arc (also called “emotional valence”) of a text by giving each word a different score. For example, on a scale of -1 to 1, “terrible” might score -1 and “amazing” might score 1. A more neutral word like “okay” would score closer to 0. I chose translations by Alexander Pope, Samuel Butler, and Emily Wilson, published in 1725, 1900, and 2017 respectively. I wanted to explore how the translators’ working in different time periods and having different life experiences might affect their interpretations of the text.
Recommended Citation
Shaheen, Erin, "Lost in Translation: Using Sentiment Analysis to Analyze Translations of Homer’s Odyssey" (2019). IPHS 300: Artificial Intelligence for the Humanities: Text, Image, and Sound. Paper 17.
https://digital.kenyon.edu/dh_iphs_ai/17
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