Visual Analysis Of Reviews

Online review platforms,with the help of millions of monthly active users,are pro-ducing millions of valuable reviews every month on restaurants,scenery spots,movies,products,or other items.Text visual analysis based on these user generated reviews aims to provide insights into all aspects of life,such as clothing,food,shelter,and transporta-tion,which is still a challenging problem.According to different research perspectives,methods on visual analysis of reviews can be divided into three aspects:word-based text visual analysis,sentiment-based text visual analysis,and spatiotemporal-characteristic-based text visual analysis.Firstly,word-based text visual analysis focuses on revealing main aspects and relationships between these aspects;Secondly,sentiment-based text vi-sual analysis aims to automatically gauge and summarize sentiments and their temporal trends for product analysis,public opinion analysis and public emotion analysis;Finally,spatiotemporal-characteristic-based text visual analysis studies on effectively combining spatiotemporal information to enhance situational awareness and assist making decisions.This paper focuses on the review data and conducts research around the above three aspects.The main contributions of the paper are summarized as follows:· This paper proposes a word-based text visual analysis method based on a semantic word cloud.Word clouds can effectively display important contents of the text.However,words are related to each other instead of being independent.Thus,the semantic word clouds can better describe the semantic information of words and the main aspects of the text.In this paper,distributed word representations are used to characterize the semantic meanings of words,and then the word similarity graph is constructed.After that,the aspects are extracted and words are arranged based on the word similarity graph,so that the semantic word cloud can lay out words in a more compact and aesthetic manner.Finally,the semantic word cloud integrates intuitive interactions to guide users to quickly read and understand the text.· This paper provides a sentiment-divergence-based text visual analysis method to explore the controversy in reviews.Statistical analysis based on ratings is one of the main methods to explore the controversy in reviews.It can quickly identify whether the controversy occurs in reviews.Sentiment analysis based on review texts can describe and summarize the causes of the controversy.This paper pro-poses a visual analysis system,and uses a quantitative analysis method based on ratings to characterize the temporal trends of the controversy and a new aspect-based sentiment analysis method to identify aspect-level reasons garnered from review texts that explain why the controversy occurs.This method interactively explores the time-evolving trend of the controversy and the aspects with the senti-ment divergence,which helps users understand and gain insights into the contro-versy in reviews.· This paper presents a text visual analysis method of spatiotemporal urban topics in reviews.Since reviews of businesses or scenery spots often have geographic location and timestamped information,the exploration of spatiotemporal charac-teristics in these reviews facilitates cultural trend discovery,location mining,and decision making.This paper proposes a visual analysis system to analyze tem-poral and spatial characteristics of reviews at the city level.Due to the diversity of characteristics of users and cities,this paper first supports topic specifying by users,and then leverages sentiment analysis and statistical analysis to characterize the temporal trend as well as geographical distributions of the user-specific topic and its sentiment.Finally,the proposed system allows the user to interactively ex-plore the temporal frequency trend and characteristic geographical distributions of a topic in reviews.