DOI:10.20894/IJDMTA.
Periodicity: Bi Annual.
Impact Factor:
SJIF:4.893 & GIF:0.787
Submission:Any Time
Publisher: IIR Groups
Language: English
Review Process:
Double Blinded
Individuals, organizations, companies are using facebook media for sharing information and utilize it to improve their marketing strategy. Likes, share and followers provide the opinions of the products or service which turns to an encouragement for the development of that companies or organizations. Using the number of likes and shares of a particular product, its popularity can be easily predicted. It is very helpful for the companies to assess their performance and also to campaign their product in the society. It will be useful not only for companies but also for the customers. It also highlights the importance of the product reviews which gains more attention by the product buyers to decide whether to buy the intended product or not based on their various aspects of the product. For example, monitor, processor speed, memory, etc are considered before buying a PC. Theis sentiment analysis of product reviews will provide nearly accurate statistics regarding a product, providing an ease to the customers for analyzing the product and zero down his/her search for an online product. In this research, a study is conducted to analyze the popularity level of website in social networking based on the posts shared on facebook to enhance the marketing strategies. Recently, data mining tools are used to identify the product rating from the customer reviews. In this paper, page ranking algorithm is used to predict product rating from online reviews.
