Cascading Behavior For Product Recommendation In Online Social Network
Online social network (OSN) is a prominent source not only sharing the feelings and common thoughts but also to share the expression and reviews about the product purchased from e-commerce sites and services utilized by the service providers. Sentiment analysis plays an important role to promote the product based on the review comments shared by the buyers. Most of the novice-buyers would like to go for getting the feedback or reviews from the known sources who purchased the product. This would become increasingly important for product market also. Though there are different forms by which the sentiment analysis helps to find the demand of a product and/or service, the cascading behavior is one such measure that can be used to recommend the product and hence it can also be used for promoting the product. This is a vital part of the manufacturing sector to understand the product demand in the market for its sustenance. This research is focused on analyzing the product reviews shared by the users for the e-commerce service provider. The results obtained through the research is showing that the cascading behavior is providing promising results based on the dataset taken for study.