Universiti Teknologi Malaysia Institutional Repository

Sentiment analysis using term based method for customers’ reviews in amazon product

Sinnasamy, Thilageswari and Amir Sjaif, Nilam Nur (2022) Sentiment analysis using term based method for customers’ reviews in amazon product. International Journal of Advanced Computer Science and Applications, 13 (7). pp. 685-691. ISSN 2158-107X


Official URL: http://dx.doi.org/10.14569/IJACSA.2022.0130780


Customers’ review in Amazon platform plays an important role for making online purchase decision making, however the reviews are snowballing in E-commerce day by day. The active sharing of customers’ experience and feedback helps to predict the products and retailers’ quality by using natural language processing. This paper will focus on experimental discussion on Amazon products reviews analysis coupled with sentiment analysis using term-based method and N-gram to achieve best findings. The investigation of sentiment analysis on amazon product gain more valuable information on related text to solve problem related services, products information and quality. The analysis begins with data pre-processing of Amazon products reviews then feature extraction with POS tagging and term-based concept. e-Commerce customer’s reviews normally classify different experience into positive, negative and neutral to judge human behavior and emotion towards the purchase products. The major findings discussed in this journal will be using four different classifier and N-grams methods by computing accuracy, precision, recall and F1-Score. TF-IDF method with N-gram shows unigram with Support Vector Machine learning with highest accuracy results for Amazon product customers’ reviews.

Item Type:Article
Uncontrolled Keywords:e-commerce, n-gram, sentiment analysis
Subjects:T Technology > T Technology (General)
Divisions:Razak School of Engineering and Advanced Technology
ID Code:100896
Deposited By: Narimah Nawil
Deposited On:18 May 2023 04:19
Last Modified:18 May 2023 04:19

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