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Can I read A framework for big data analytics in commercial social networks: A case study on sentiment analysis and fake review detection for marketing decision-making on EtoBox?
A framework for big data analytics in commercial social networks: A case study on sentiment analysis and fake review detection for marketing decision-making by Erick Kauffmann; Jesús Peral; David Gil; Antonio Ferrández; Ricardo Sellers; Higinio Mora is a Business, Management and Accounting article available to read on EtoBox.
What is A framework for big data analytics in commercial social networks: A case study on sentiment analysis and fake review detection for marketing decision-making about?
User-generated content about brands is an important source of big data that can be transformed into valuable information. A huge number of items are reviewed and rated by consumers on a daily basis, and managers have a keen interest in real-time monitoring of this information to improve decision-making. The main challenge is to mine reliable textual consumer opinions, and automatically use them to rate the best products or brands. We propose a framework to automatically analyse these reviews, transforming negative and positive user opinions in a quantitative score. Sentiment analysis was employed to analyse online reviews on Amazon. The Fake Review Detection Framework-FRDF-detects and removes fake reviews using Natural Language Processing technology. The FRDF was tested on reviews of products from high-tech industries. Brands were rated according to consumer sentiment. The findings demonstrate that brand managers and consumers would find this tool useful, in combination with the 5-Star score, for more comprehensive decision-making. For instance, the FRDF ranks the best products by price alongside their respective sentiment value and the 5-Star score.
Who reads A framework for big data analytics in commercial social networks: A case study on sentiment analysis and fake review detection for marketing decision-making?
It is typically read by researchers, students, and practitioners in Business, Management and Accounting.
- Author
- Erick Kauffmann; Jesús Peral; David Gil; Antonio Ferrández; Ricardo Sellers; Higinio Mora
- Publisher
- Elsevier BV
- Published
- 2020
- Language
- EN
- Field
- Business, Management and Accounting (Social Sciences)