Detection of fake online hotel reviews
Anna V. Sandifer, Casey Wilson, Aspen Olmsted · 2017
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.