Recognition and rating of Amazon product reviews
Abstract
The flow of information arises every day through the internet continuously thanks to the constant interactions between users, these interactions are presented in comments that can be positive or negative. This can help a lot to the service offered by Amazon on their products to understand if this' in good condition or not, so that its users of the platform can be convinced when buying a product, and is that, if these are a large number, an analysis made by one person is not enough. This requires the use of tools that operate with large amounts of data such as (name of data processing), which is a model that helps the analysis of classification of comments based on what users express. In this paper we will use' this model for the classification of Amazon product reviews, rating these reviews based on their description. It will also make use of metrics and future suggestions for the proposal mentioned in this paper. The analysis of comments will help to understand how people classify these different situations in their daily lives. Social network data is used throughout the analysis and classification process, which consists of text data. Using social networks, comments can be monitored or analyzed. In this research work, we will classify the data of comments made on Amazon relating to their rating on each comment.
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References
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