Volume-8, Issue-2 (July-December)
2021
Pages: 25-33
Open Access
CONSUMER SENTIMENT ANALYSIS THROUGH REVIEWS ON BLOGS AND SOCIAL MEDIA FOR ONLINE SHOPPING IN THE UAE
Jitendra Singh Rathore, Rajita Srivastava
India
Abstract
Abstract
The massive acceptance of blogs and social mediaunlocks the access for consumers to express their
opinions and views about the happiness or disappointment of online shopping. Sentiments of blogs
and social mediaare instantaneous and economically feasible than the traditional technique of
collecting responses. Consumers in the UAE are prone to use blogs and social mediafor giving
feedback and responses about the products purchased online. The research thus finds its importance in
the context and uses two research hypotheses to recognize the applicability of blogs and social
mediaas a tool for online responses. Three industry sectors, electronics, fashion, and travel, are taken
in the research for comprehensive analysis. Overall, 1200 responses are collected from 4 blogs (based
on the sector), and another 1200 responses are from 4 social media channels (Facebook, Twitter,
YouTube, and Instagram). The responses are analyzed using the QDAP (Quantitative Discourse
Analysis Package) dictionary in R programming.
Keywords: QDAP, t_test, online-based-brand community (OBBC), s-commerce, sentiment analysis,
two-tailed hypotheses test.
The massive acceptance of blogs and social mediaunlocks the access for consumers to express their
opinions and views about the happiness or disappointment of online shopping. Sentiments of blogs
and social mediaare instantaneous and economically feasible than the traditional technique of
collecting responses. Consumers in the UAE are prone to use blogs and social mediafor giving
feedback and responses about the products purchased online. The research thus finds its importance in
the context and uses two research hypotheses to recognize the applicability of blogs and social
mediaas a tool for online responses. Three industry sectors, electronics, fashion, and travel, are taken
in the research for comprehensive analysis. Overall, 1200 responses are collected from 4 blogs (based
on the sector), and another 1200 responses are from 4 social media channels (Facebook, Twitter,
YouTube, and Instagram). The responses are analyzed using the QDAP (Quantitative Discourse
Analysis Package) dictionary in R programming.
Keywords: QDAP, t_test, online-based-brand community (OBBC), s-commerce, sentiment analysis,
two-tailed hypotheses test.