Detection of fake online hotel reviews

Anna V. Sandifer, Casey Wilson, Aspen Olmsted
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引用次数: 8

Abstract

Individuals use online reviews to make decisions about available products and services. In recent years, businesses and the research community have shown a great amount of interest in the identification of fake online reviews. Applying accurate algorithms to detect fake online reviews can protect individuals from spam and misinformation. We gathered filtered and unfiltered online reviews for several hotels in the Charleston area from yelp.com. We extracted part-of-speech features from the data set, applied three classification models, and compared accuracy results to related works.
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检测虚假在线酒店评论
个人使用在线评论来对可用的产品和服务做出决定。近年来,企业和研究界对识别虚假在线评论表现出了极大的兴趣。应用精确的算法来检测虚假的在线评论可以保护个人免受垃圾邮件和错误信息的侵害。我们从yelp.com上收集了查尔斯顿地区几家酒店经过过滤和未经过滤的在线评论。我们从数据集中提取词性特征,应用三种分类模型,并将准确率结果与相关工作进行比较。
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