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Sentiment Analysis of Indonesian New Capitol (IKN) Tweets by Stacked Generalization of Deep Learning

Published: 27 February 2023 Publication History

Abstract

The increasing use of Twitter for conveying the general public's sentiment toward a specific public policy generates pros and cons and has led to much research in sentiment analysis. Instead of exploring the most suitable classifier for a sentiment analysis model individually, there is a trend of employing an ensemble of classifiers to improve the accuracy and performance of the model. We proposed a model, initially by training word embedding using word2vec from 12.5K Indonesian Twitter on the relocation issue of the new capitol city of Indonesia (IKN) and by utilizing CNN, Bidirectional LSTM, and MLP as the base classifiers. Finally, we performed a stack generalization ensemble technique using MLP and LR as the meta-classifiers and compared the performance of the ensemble techniques with individual base classifiers. The base classifiers take advantage of the weights the word embedding provides to do the learning process. The results show that the stacking ensemble using MLP performs slightly better than LR as the meta-classifier, with the F-1 score of 74.65% vs. 73.78%, respectively. MLP meta-classifiers also perform somewhat better than the hard and soft majority voting ensemble with difference F-1 scores of 3.75% and 2.56%, respectively. The results show that the proposed stacked generalization technique model has improved the performance of the sentiment analysis model.

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References

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Cited By

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  • (2023)Top Layer Selection in Pretrained Models for Sentiment Analysis on Biodiversity Tweets in Bahasa Indonesia2023 International Conference on Computer, Control, Informatics and its Applications (IC3INA)10.1109/IC3INA60834.2023.10285786(149-154)Online publication date: 4-Oct-2023

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IC3INA '22: Proceedings of the 2022 International Conference on Computer, Control, Informatics and Its Applications
November 2022
415 pages
ISBN:9781450397902
DOI:10.1145/3575882
© 2022 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Published: 27 February 2023

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Author Tags

  1. Deep Learning
  2. Ensemble technique
  3. Meta Learner
  4. Sentiment Analysis
  5. Stacked Generalization
  6. Twitter
  7. Word2Vec

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  • (2023)Top Layer Selection in Pretrained Models for Sentiment Analysis on Biodiversity Tweets in Bahasa Indonesia2023 International Conference on Computer, Control, Informatics and its Applications (IC3INA)10.1109/IC3INA60834.2023.10285786(149-154)Online publication date: 4-Oct-2023

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