Article
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Word Vectors for Criticism of a Korean Film - 'Decision to Leave' by Chanwook Park
Version 1
: Received: 23 November 2023 / Approved: 24 November 2023 / Online: 24 November 2023 (11:28:04 CET)
How to cite: Ko, K.; Paik, J. Word Vectors for Criticism of a Korean Film - 'Decision to Leave' by Chanwook Park. Preprints 2023, 2023111558. https://doi.org/10.20944/preprints202311.1558.v1 Ko, K.; Paik, J. Word Vectors for Criticism of a Korean Film - 'Decision to Leave' by Chanwook Park. Preprints 2023, 2023111558. https://doi.org/10.20944/preprints202311.1558.v1
Abstract
This research presents a novel approach to film analysis, leveraging word vectors to objectively evaluate movie critiques. Focusing on Director Chanwook Park’s award-winning film, ’Decision to Leave’, the study employs word vectors derived from the movie’s script of Korean text. Traditional critiques often emphasize contrasting elements and themes, but their subjective nature poses challenges in objective validation. To address this, we trained a language model using LSTM on the film’s script, obtaining word vectors that capture the essence of the narrative. These vectors were then used to perform various text analyses, including similarity and analogy operation for the keywords suggested by the critiques. By comparing the semantic relationships in the critiques with those derived from the word vectors, we could objectively validate the critiques’ assertions. Furthermore, we visualized the word vectors in a two-dimensional space, confirming the spatial relationships of key terms highlighted in critiques. The study underscores the potential of word vectors in providing a more objective lens for film analysis, bridging the gap between traditional film criticism and data-driven insights.
Keywords
Analogy operation; chanwook park; 'decision to leave'; film criticism; korean film; language model; LSTM; similarity operation; word vector
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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