CSE 255 Assignment 1: Helpfulness in Amazon Reviews
نویسندگان
چکیده
In this paper we consider models for predicting the helpfulness rating of Amazon book reviews. We examine features such as the review’s star rating, the length of the review text, the readability of the review text, and the amount of comparisons made in the review. We compare Support Vector Machine and Random Forests models both for regression and classification.
منابع مشابه
Predicting Amazon review helpfulness
Reviews on amazon are ranked by how helpful they are rated by users in an effort to quickly summarize the opinions of a product for potential buyers. This project aims to explore what factors affect a review’s helpfulness by building a classification model on the Amazon movie reviews data set. The model performs well with accuracies over 85% and it is found that a review’s writing style, produc...
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There is a lot of evidence that people place great weight on online user reviews. And yet there are many reports of mischief in reviews, such as the January 2009 incident with a Belkin manager publicly offering sixty-five cents for positive reviews of their products. Is the high level of trust warranted when there are so many motives and opportunities for manipulating reviews? That question mot...
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Online reviews have become essential aspect in E-commerce platforms due to its role for assisting customers’ buying choices. Furthermore, the most helpful reviews that have some attributes are support customers buying decision; therefore, there is needs for investigating what are the attributes that increase the Review Helpfulness (RH). This research paper proposed novel model called inclusive ...
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