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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

Word-Level Contextual Sentiment Analysis with Interpretability

February 1, 2023

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Authors

Tomoki Ito

The University of Tokyo


Kota Tsubouchi

Yahoo Japan Corporation


Hiroki Sakaji

The University of Tokyo


Tatsuo Yamashita

Yahoo Japan Corporation


Kiyoshi Izumi

The University of Tokyo


DOI:

10.1609/aaai.v34i04.5845


Abstract:

Word-level contextual sentiment analysis (WCSA) is an important task for mining reviews or opinions. When analyzing this type of sentiment in the industry, both the interpretability and practicality are often required. However, such a WCSA method has not been established. This study aims to develop a WCSA method with interpretability and practicality. To achieve this aim, we propose a novel neural network architecture called Sentiment Interpretable Neural Network (SINN). To realize this SINN practically, we propose a novel learning strategy called Lexical Initialization Learning (LEXIL). SINN is interpretable because it can extract word-level contextual sentiment through extracting word-level original sentiment and its local and global word-level contexts. Moreover, LEXIL can develop the SINN without any specific knowledge for context; therefore, this strategy is practical. Using real textual datasets, we experimentally demonstrate that the proposed LEXIL is effective for improving the interpretability of SINN and that the SINN features both the high WCSA ability and high interpretability.

Topics: AAAI

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HOW TO CITE:

Tomoki Ito||Kota Tsubouchi||Hiroki Sakaji||Tatsuo Yamashita||Kiyoshi Izumi Word-Level Contextual Sentiment Analysis with Interpretability Proceedings of the AAAI Conference on Artificial Intelligence (2020) 4231-4238.

Tomoki Ito||Kota Tsubouchi||Hiroki Sakaji||Tatsuo Yamashita||Kiyoshi Izumi Word-Level Contextual Sentiment Analysis with Interpretability AAAI 2020, 4231-4238.

Tomoki Ito||Kota Tsubouchi||Hiroki Sakaji||Tatsuo Yamashita||Kiyoshi Izumi (2020). Word-Level Contextual Sentiment Analysis with Interpretability. Proceedings of the AAAI Conference on Artificial Intelligence, 4231-4238.

Tomoki Ito||Kota Tsubouchi||Hiroki Sakaji||Tatsuo Yamashita||Kiyoshi Izumi. Word-Level Contextual Sentiment Analysis with Interpretability. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.4231-4238.

Tomoki Ito||Kota Tsubouchi||Hiroki Sakaji||Tatsuo Yamashita||Kiyoshi Izumi. 2020. Word-Level Contextual Sentiment Analysis with Interpretability. "Proceedings of the AAAI Conference on Artificial Intelligence". 4231-4238.

Tomoki Ito||Kota Tsubouchi||Hiroki Sakaji||Tatsuo Yamashita||Kiyoshi Izumi. (2020) "Word-Level Contextual Sentiment Analysis with Interpretability", Proceedings of the AAAI Conference on Artificial Intelligence, p.4231-4238

Tomoki Ito||Kota Tsubouchi||Hiroki Sakaji||Tatsuo Yamashita||Kiyoshi Izumi, "Word-Level Contextual Sentiment Analysis with Interpretability", AAAI, p.4231-4238, 2020.

Tomoki Ito||Kota Tsubouchi||Hiroki Sakaji||Tatsuo Yamashita||Kiyoshi Izumi. "Word-Level Contextual Sentiment Analysis with Interpretability". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.4231-4238.

Tomoki Ito||Kota Tsubouchi||Hiroki Sakaji||Tatsuo Yamashita||Kiyoshi Izumi. "Word-Level Contextual Sentiment Analysis with Interpretability". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 4231-4238.

Tomoki Ito||Kota Tsubouchi||Hiroki Sakaji||Tatsuo Yamashita||Kiyoshi Izumi. Word-Level Contextual Sentiment Analysis with Interpretability. AAAI[Internet]. 2020[cited 2023]; 4231-4238.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
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