A survey of quality prediction of product reviews

Hana Almagrabi, A Malibari, John McNaught

    Research output: Contribution to journalArticlepeer-review


    With the help of Web-2.0, the Internet offers a vast amount of reviews on many topics and in different domains. This has led to an explosive growth of product reviews and customer feedback, which presents the problem of how to handle the abundant volume of data. It is an expensive and time-consuming task to analyze this huge content of opinions. Therefore, the need for automated sentiment analysis systems is vital. However, these systems encounter many challenges; assessing the content quality of the posted opinions is an important area of study that is related to sentiment analysis. Currently, review helpfulness is assessed manually; however the task of automatically assessing it has gained more attention in recent years. This paper provides a survey of approaches to the challenge of identifying the content quality of product reviews.
    Original languageEnglish
    Article number7
    Pages (from-to)49-58
    Number of pages9
    JournalInternational Journal of Advanced Computer Science and Applications
    Issue number11
    Publication statusPublished - Nov 2015


    • sentiment analysis
    • product reviews
    • content analysis
    • helpfulness detection


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