Journal of Data Science and Its Applications
Vol 3 No 2 (2020): Journal of Data Science and Its Applications

Aspect Based Sentiment Analysis on Beauty Product Review Using Random Forest

Anggitha Yohana Clara (Telkom University)
Adiwijaya Adiwijaya (Unknown)
Mahendra Dwifebri Purbolaksono (Unknown)

Article Info

Publish Date
30 Jul 2020


Cosmetics and beauty products (including skincare) are the products used as body care or face care and used to accentuate the body alure. A product could give diverse sentiment to the consumers including positive and negative sentiment. Many consumers of beauty products are sharing their reviews to help other consumers to find the right products to buy and to give feedback to the brand of the beauty product itself. The number of reviews is inversely proportional to the lack of opinion identification towards product’s aspects. Hence, a study has been conducted to analyze beauty products reviews as toner, serum, sun protection, and exfoliator. The analysis process is conducted aspect based to determine sentiment towards aspect of beauty products based on the reviews. The result is addressed to people using skincare and beauty product brands in deducting consumer’s opinion. The solution to this problem is by using Random Forest with hyperparameters tuning as classification method, and TF-IDF and n-gram as feature extraction methods. The multi-aspect sentiment analysis in this study obtained highest accuracy for 90.48%, precision for 87.27%, recall for 70.13%, and F1-Score for 71.77%.

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Journal Info





Computer Science & IT Decision Sciences, Operations Research & Management


JDSA welcomes all topics that are relevant to data science, computational linguistics, and information sciences. The listed topics of interest are as follows: Big Data Analytics Computational Linguistics Data Clustering and Classifications Data Mining and Data Analytics Data Visualization ...