Unifying Topic, Sentiment & Preference in an HDP-Based Rating Regression Model for Online Reviews

by   Zheng Chen, et al.

This paper proposes a new HDP based online review rating regression model named Topic-Sentiment-Preference Regression Analysis (TSPRA). TSPRA combines topics (i.e. product aspects), word sentiment and user preference as regression factors, and is able to perform topic clustering, review rating prediction, sentiment analysis and what we invent as "critical aspect" analysis altogether in one framework. TSPRA extends sentiment approaches by integrating the key concept "user preference" in collaborative filtering (CF) models into consideration, while it is distinct from current CF models by decoupling "user preference" and "sentiment" as independent factors. Our experiments conducted on 22 Amazon datasets show overwhelming better performance in rating predication against a state-of-art model FLAME (2015) in terms of error, Pearson's Correlation and number of inverted pairs. For sentiment analysis, we compare the derived word sentiments against a public sentiment resource SenticNet3 and our sentiment estimations clearly make more sense in the context of online reviews. Last, as a result of the de-correlation of "user preference" from "sentiment", TSPRA is able to evaluate a new concept "critical aspects", defined as the product aspects seriously concerned by users but negatively commented in reviews. Improvement to such "critical aspects" could be most effective to enhance user experience.


page 1

page 2

page 3

page 4


Large-Scale Joint Topic, Sentiment & User Preference Analysis for Online Reviews

This paper presents a non-trivial reconstruction of a previous joint top...

Identifying Restaurant Features via Sentiment Analysis on Yelp Reviews

Many people use Yelp to find a good restaurant. Nonetheless, with only a...

Enhancing Collaborative Filtering Recommender with Prompt-Based Sentiment Analysis

Collaborative Filtering(CF) recommender is a crucial application in the ...

Psychologically-Inspired Causal Prompts

NLP datasets are richer than just input-output pairs; rather, they carry...

Every Bite Is an Experience: Key Point Analysis of Business Reviews

Previous work on review summarization focused on measuring the sentiment...

Stars Are All You Need: A Distantly Supervised Pyramid Network for Document-Level End-to-End Sentiment Analysis

In this paper, we propose document-level end-to-end sentiment analysis t...

Painsight: An Extendable Opinion Mining Framework for Detecting Pain Points Based on Online Customer Reviews

As the e-commerce market continues to expand and online transactions pro...

Please sign up or login with your details

Forgot password? Click here to reset