| dc.description.abstract | With the development of the internet economy, various websites accumulate tons of reviews about different product and service. Those reviews have become one major information source besides official product information, expert opinion, and automatically generated individualized advice. The survey shows that percentage of gathering buying information on internet gradually increases by years, and the relevant researchers have also proven that consumers pay more attention to others’ reviews, thus deeply affect consumers’ shopping decision. Unfortunately, by taking advantage of this trend , some dealers manipulate reviews in order to exaggerate their own product or defame their rivals. Those behaviors have brought severe damage to consumers and commerce.
This study takes fake reviews as research object, using grammar and style stamp as cutting angle, and discusses the differences between fake reviews and real reviews. Take real reviews on America website “TripAdvisor” and the comparison group “Fake reviews” as analysis objects, and extract 3 major points: unique vocabulary, specific quantifier, and noun verb ratio. Deal those reviews with character prospect technique and build up a model which can automatically classify fake reviews.
The result, generated by developed model in this research, shows that the more unique vocabulary and specific quantifier and noun it contains, the less possibility it is fake. | en_US |