Online review analysis on various networks' consumer feedback using deep learning. Issue 6 (6th September 2022)

• Record Type: Journal Article
• Authors: Liu, Huajin
• Is Part Of: IET networks. Volume 11:Issue 6(2022)
• Page Start: 234
• Page End: 244
• Publication Date: 2022-09-06
• Subjects: computer networks -- consumer feedback analysis -- deep learning -- edge computing -- online review -- sentimental analysis; Computer network architectures -- Periodicals; Computer network protocols -- Periodicals; Information networks -- Periodicals; Telecommunication systems -- Periodicals; 004.605
• DOI: 10.1049/ntw2.12045
• Languages: English
• ISSNs: 2047-4954

Abstract

Abstract: In order to understand the application of deep learning in consumer online review analysis, the text content of online review and the impact of national culture on it are studied. A consumer online comment analysis model based on deep learning is constructed and utilised using edge computing. With the online reviews of mobile phone and computer products as the case, the analysis is made. The data of online reviews on various network platforms is obtained. The model based on edge computing is used for analysis, and the results of product feature sentiment analysis are obtained. The results show that the deep learning model can achieve effective product feature extraction and high accuracy sentiment analysis, which is reasonable and effective in practical application.