Summarizing Online Customer Review using Topic Modeling and Sentiment Analysis

Abstract

With the massive implementation of social media in various forms in various business domains, business or product owners have the opportunity to be able to take advantage of user review data that is available free of charge to evaluate the products they issue. User reviews on social media platforms, marketplaces, and e-commerce are User Generated Content (UGC) which is very useful for product owners to find out the extent of user preferences for their products. However, to be able to comprehensively read the data, the right technology is needed considering that the data is in the form of text in very large quantities. Reading one by one and then drawing conclusions is certainly not the right approach because it will take quite a lot of time. So, in this study, the researcher will use a text analysis-based approach, especially topic modeling and sentiment analysis to summarize user reviews in the comments or reviews column on the e-commerce platform. The case study used in this study is user reviews in the comments column on the Amazon site for the Lenovo K8 Note smartphone product. From the experiments carried out, the approach used can summarize the reviews written by quite many users in one summary that can be easily understood.