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With the continuous development of online shopping, analyzing the competitiveness of products in the fierce market competition is becoming increasingly crucial to position their own product development. However, the information overload brought by the network development makes it getting difficult to obtain the accurate competitiveness information. Therefore, competitiveness analysis research to combine with the perceived helpfulness study needs urgent solution. Furthermore, deviations exist in the three common methods of perceived helpfulness research. Finally, the traditional information fusion analysis only analyzes the advantages and disadvantages of products in competitiveness analysis without taking account of the competitive environment.

This study puts forward a novel prediction model of perceived helpfulness in conjunction of unsupervised learning and sentiment analysis techniques, to conduct the comparison with pros and cons of congeneric products.

This paper adopts Wilcoxon test to demonstrate the significant rectification of our competitiveness analysis to the traditional methods. It is noted that the positive reviews of the products in this study impact more on product word of mouth and competitiveness than negative ones.

To sum up, the results of this study benefit businesses in locating their dynamic market position with competitors in practice and exploring new method for long-term development strategic planning.