Data Exploration of online product reviews and prospective

  • Vidya Kamma, D. Teja Santosh, Sridevi Gutta

Abstract

The online shopping websites of today are providing one of many information services by writing the consumer review and encouraging rapid growth through the general comments of consumers [1]. For better understanding of these consumer reviews the available relationships among the crucial pieces of the review namely product aspects and opinions are to be explored. Reviewing and implementing content-based recommendations has a major impact on consumer opinions written on product reviews today [2]. Visual exploring these crucial pieces helps to uncover the nous and adjectives written in them. Subsequently, the quantified details of these adjectives are useful in downstream task of machine learning [3] in predicting the product recommendations. However, many text explorations have produced and visualized the characteristics and the outputs of the language model [4] namely word count, character length, word sequences. By profiling the reviews data by using summarization techniques and analyzing the expected relationships the corresponding insights are obtained in the clearer manner. The focus of this Exploratory Data Analysis (EDA) is to explore the crucial pieces of reviews which are nouns and adjectives scripted by the reviewers and to understand the polarities of these pieces so that the statistical recommendations based on polarities (aggregated to sentiments) are useful in explaining the obtained recommendations by using ontological analysis.

Published
2021-08-25
How to Cite
Sridevi Gutta, V. K. D. T. S. (2021). Data Exploration of online product reviews and prospective. Design Engineering, 3918-3931. Retrieved from http://thedesignengineering.com/index.php/DE/article/view/3753
Section
Articles