Aspect-Based Sentiment Analysis on Indonesian Restaurant Review Using a Combination of Convolutional Neural Network and Contextualized Word Embedding

Abstract

Someone's opinion on a product or service that is poured through a review is something that is quite important for the owner or potential customer. However, the large number of reviews makes it difficult for them to analyze the information contained in the reviews. Aspect-based sentiment analysis is the process of determining the sentiment polarity of a sentence based on predetermined aspects.This study aims to analyze an Indonesian restaurant review using a combination of Convolutional Neural Network and Contextualized Word Embedding models. Then it will be compared with a combination of Convolutional Neural Network and Traditional Word Embedding models. The result of aspect-classification on three models; BERT-CNN, ELMo-CNN, and Word2vec-CNN give the best results on the ELMo-CNN model with micro-average precision of 0.88, micro-average recall of 0.84, and micro-average f1-score of 0.86. Meanwhile, the sentiment-classification gives the best results on the BERT-CNN model with a precision value of 0.89, a recall of 0.89, and an f1-score of 0.91. Classification using data without stemming have almost similar results, even better than using data with stemming.

Aspect-Based Sentiment Analysis on Application Review using Convolutional Neural Network

“…The ABSA process can be done by classifying aspects and sentiments. The model used will classify text documents into category aspects and sentiment tendencies [7]. For example, in the review sentence "The food price is quite high", the ABSA model will classify the sentence into price aspects and negative sentiment classes [7].…”

“…The model used will classify text documents into category aspects and sentiment tendencies [7]. For example, in the review sentence "The food price is quite high", the ABSA model will classify the sentence into price aspects and negative sentiment classes [7]. This method requires labeled text data to train the model used in ABSA.…”

“…The research flow used in this study is an adaptation of a research journal [7], [8] with several adjustments. The following is the steps that describes the flow of this research: Functionalitye-Hac…”

“…The ABSA process is mainly done by classifying aspects and sentiments. The algorithm model used will classify the text into category aspects and then determine the sentiment [7].…”

Analisis Sentimen Review Tempat Wisata Pada Data Online Travel Agency Di Yogyakarta Menggunakan Model Neural Network IndoBERTweet Fine Tuning

“…Pada tahap evaluasi model digunakan untuk mengetahui akurasi algoritma dilakukan evaluasi akurasi, presisi, dan recall untuk menghasilkan kesimpulan performa dari algoritma yang dipakai (Rizki Amalia and Winarko, 2021). Jika data memiliki karakteristik balance data maka metrik evaluasi eror yang cocok adalah akurasi dan untuk imbalance data maka matrik evaluasi eror yang cocok adalah F1-score.…”