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He extracted 26 features for use in his experiments by combining review content (text) features, reviewer features, and hotel information features.
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The BPG awards, now in their 40th year, are unique because they are the only ones voted for by people who write about TV and radio for a living, including reviewers, feature writers and media correspondents.
The following subsections discuss and provide examples of some review centric and reviewer centric features.
Extracting review specific and reviewer specific features [23] such as content similarity, sentiment analysis, rating deviation and brand deviation is a more robust way to identify fake reviews.
Using reviewer centric features in combination with review centric features may be preferred over a review centric only approach for spam detection.
Jindal et al. [8] also studied the impact of reviewer centric features on review spam detection.
Research by Jindal et al. [20, 21] shows that the addition of reviewer centric features yields higher classifier performance than the use of n-gram features alone, and other experiments support this conclusion [3, 9, 23].
Conversely, reviewer centric features take a holistic look at all of the reviews written by any particular author, along with information about the particular author.
Another two groups of reviewer centric features were created: profile and behavioral.
Using only reviewer centric features Fei et al. achieved an F-score of 75.4 % for burst reviews, and 68.7 % for all reviews.
Reviewer centric features have also been demonstrated to be important for accurate detection of review spam as seen in [9, 20, 21, 23, 24].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com