Sentiment Classification on Suicide Notes Using Bi-LSTM Model-Reference-Cited by-同舟云学术

Sentiment Classification on Suicide Notes Using Bi-LSTM Model

Published:2024 Issue: Volume: Page:1-10
ISSN:2367-3370
Container-title:Lecture Notes in Networks and Systems
language:en
Short-container-title:

Author:

Beniwal Rohit,Dobhal Abhishek

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-6547-2_1

Reference11 articles.

1. Hu Z, Hu J, Ding W, Zheng X (2017) Review sentiment analysis based on deep learning. In: IEEE 12th international conference on e-business engineering, Beijing, China, pp 87–94

2. Bengesi S, Oladunni T, Olusegun R, Audu H (2023) A machine learning-sentiment analysis on Monkeypox Outbreak: an extensive dataset to show the polarity of public opinion from Twitter tweets. IEEE Access 11:11811–11826

3. Garcia-Diaz JA, Garcia-Sanchez F, Valencia-Garcia R (2023) Smart analysis of economics sentiment in Spanish based on linguistic features and transformers. IEEE Access 11:14211–14224

4. Nuha U, Lin CH (2023) Aspect - Based Sentiment Analysis with Semi-Supervised Approach on Taiwan Social Distancing. International Conference on Artificial Intelligence in Information and Communication (ICAIIC), Bali, Indonesia, pp. 444–447 (2023)

5. Zhang T, Guo J (2021) Research on Chinese sentiment analysis based on Bi-LSTM net-works. In: IEEE/ACIS 20th international fall conference on computer and information science (ICIS Fall), Xi'an, China, pp 198–203

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