Product Feature Ranking and Popularity Model based on Sentiment Comments
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 9
Abstract
This paper proposes the development of a model to determine feature popularity ranking for products in the market. Each feature that is reviewed by a customer has a relation to sentiment words present in the sentences within a customer review. Feature quantity of a product, derived from customer review dataset, cannot be used as a benchmark to determine customers’ preferences since each feature is influenced by sentiment words that give it either a positive or negative meaning. A positive meaning shows that the feature is liked by user; and a negative meaning shows that it is disliked by user. This study finds that sentiment assessments by users play an important role in determining feature popularity ranking; and they affect the feature of a product. Thus, this study proposes the development of a model that takes into account the importance of sentiment assessments present in each sentence within a customer review of a product feature. A case study has been conducted in proving that the developed model is able to produce a list of product feature popularity ranking. Results of this experimental model is also put into simple comparative analysis with a few models from previous studies.
Authors and Affiliations
Siti Rohaidah Ahmad, Azuraliza Abu Bakar, Mohd Ridzwan Yaakub, Nurhafizah Moziyana Mohd Yusop, Muslihah Wook, Arniyati Ahmad
Keywords
Related Articles
- EP ID EP393832
- DOI 10.14569/IJACSA.2018.090921
- Views 69
- Downloads 0
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