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Emotion classification of Indonesian Tweets using Bidirectional LSTM

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Bibliographic Details
Main Authors: Aaron, Glenn, Phillip, LaCasse, Bruce, Cox
Format: Book
Language:English
Published: Springer 2023
Subjects:
Bidirectional LSTM
Online Access:https://link.springer.com/article/10.1007/s00521-022-08186-1
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8273
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spelling oai:localhost:PNK-82732023-04-25T03:54:53Z Emotion classification of Indonesian Tweets using Bidirectional LSTM Aaron, Glenn Phillip, LaCasse Bruce, Cox Bidirectional LSTM CC BY Emotion classification can be a powerful tool to derive narratives from social media data. Traditional machine learning models that perform emotion classification on Indonesian Twitter data exist but rely on closed-source features. Recurrent neural networks can meet or exceed the performance of state-of-the-art traditional machine learning techniques using exclusively open-source data and models. Specifically, these results show that recurrent neural network variants can produce more than an 8% gain in accuracy in comparison with logistic regression and SVM techniques and a 15% gain over random forest when using FastText embeddings. 2023-04-25T03:54:53Z 2023-04-25T03:54:53Z 2023 Book https://link.springer.com/article/10.1007/s00521-022-08186-1 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8273 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic Bidirectional LSTM
spellingShingle Bidirectional LSTM
Aaron, Glenn
Phillip, LaCasse
Bruce, Cox
Emotion classification of Indonesian Tweets using Bidirectional LSTM
description CC BY
format Book
author Aaron, Glenn
Phillip, LaCasse
Bruce, Cox
author_facet Aaron, Glenn
Phillip, LaCasse
Bruce, Cox
author_sort Aaron, Glenn
title Emotion classification of Indonesian Tweets using Bidirectional LSTM
title_short Emotion classification of Indonesian Tweets using Bidirectional LSTM
title_full Emotion classification of Indonesian Tweets using Bidirectional LSTM
title_fullStr Emotion classification of Indonesian Tweets using Bidirectional LSTM
title_full_unstemmed Emotion classification of Indonesian Tweets using Bidirectional LSTM
title_sort emotion classification of indonesian tweets using bidirectional lstm
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s00521-022-08186-1
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8273
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score 8.891145

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