Perceived quality and value are very essential attributes in the context of brand management. These attributes are traditionally measured using primary surveys. In this work, we propose a methodology to estimate perceived quality and value from online consumer reviews using aspect-based sentiment analysis. We crawled reviews of five popular mobile brands from a reputed e-commerce website. We have applied state-of-the-art text pre-processing techniques to clean the text and to extract the aspects using a semi-automatic approach using dependency parser. The aspects are categorized into five clusters in relevance with benefits consumers get from the brand. Lastly, we have applied TOPSIS, a multi-criterion decision-making algorithm, to rank the brands based on perceived quality scores.
CITATION STYLE
Mitra, S., & Jenamani, M. (2020). A Method to Estimate Perceived Quality and Perceived Value of Brands to Make Purchase Decision Using Aspect-Based Sentiment Analysis. In Lecture Notes in Networks and Systems (Vol. 103, pp. 447–454). Springer. https://doi.org/10.1007/978-981-15-2043-3_49
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