We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
SENTIMENT ANALYSIS OF ONLINE PRODUCT REVIEW USING DEEP LEARNING IN DISTRIBUTED SENSOR NETWORKS.
- Authors
JUN YAO
- Abstract
Recently, sentiment analysis has been a major business practice for an organization that helps analyze online reviews of different products. An organization can understand the customer's perception of their organizational products by analyzing reviews. On the other hand, this analysis process also helps to understand the customer's emotions about the organizational products. In this process, deep learning and distributed sensor networks play crucial roles in analyzing emotions. Five different steps of this analysis will provide accurate information about the customers' emotions on products. This analysis will help increase the product's value by understanding the customer's perception of where negative feedback improves the products. Through the help of this analysis, an organization will get several benefits that enrich its organizational image. On the other hand, this analysis process will face polarity issues, tone issues, comparative sentence analysis issues, and understanding idioms and emojis issues. The implementation of live API and proper sentiment analysis tools help to increase the effectiveness of this analysis.
- Subjects
DEEP learning; SENSOR networks; SENTIMENT analysis; PRODUCT reviews; CONSUMERS' reviews; DISTRIBUTED sensors; NATURAL language processing
- Publication
Scalable Computing: Practice & Experience, 2023, Vol 24, Issue 4, p1117
- ISSN
1895-1767
- Publication type
Article
- DOI
10.12694/scpe.v24i4.2386