Data Analysis of online product reviews

Abstract

Visual exploration of the content of the online product reviews is one of the most important tasks in text mining and specifically in sentiment analysis research. However, many text explorations have produced and visualized the characteristics and the outputs of the language model namely word count, character length, word sequences and so on. The main focus of this exploratory data analysis is to explore the crucial pieces of reviews information namely nouns and adjectives scripted by the reviewers and to understand the opinion orientations of the aspects. These are useful in determining the statistical recommendations based on sentiments. The research prospective gained from this exploratory analysis is that the statistical recommendations be explained by using expressive semantic web rules of the ontology in the model-agnostic manner