2015 6th International Conference on Computing, Communication and Networking Technologies (ICCCNT) 2015
DOI: 10.1109/icccnt.2015.7395179
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Distinguishing between authentic and fictitious user-generated hotel reviews

Abstract: Distinguishing between authentic and fictitious user-generated hotel reviews

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Cited by 4 publications
(7 citation statements)
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“…This suggests that users can be skeptical about reviews that offer overly specific details. Perhaps, the veracity of such informative reviews is doubted because they are viewed as being written by individuals who are too eager to convince (Banerjee et al, 2015).…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…This suggests that users can be skeptical about reviews that offer overly specific details. Perhaps, the veracity of such informative reviews is doubted because they are viewed as being written by individuals who are too eager to convince (Banerjee et al, 2015).…”
Section: Resultsmentioning
confidence: 99%
“…Users appear to trust reviews that are congruent with their expectation-in this paper, positive reviews for luxury hotels, and negative reviews for budget hotels-easily without basing their decision-making adequately on their perception. This might not always be wise as several reviews available on the Internet could be biased (Banerjee et al, 2015;Pal & Chua, 2016).…”
Section: Implications For Practicementioning
confidence: 99%
“…The initial pool of 83 variables was filtered through information gain (IG) and chi-squared (v 2 ) feature selection techniques. Only those variables with nonzero IG and nonzero v 2 values were selected for further investigation (Banerjee, Chua, & Kim, 2015;Forman, 2003;O'Mahony & Smyth, 2009). 1 Second, the feature-selected variables were further tested using independent samples t-tests to identify a filtered set of linguistic variables that differed between authentic and fictitious reviews.…”
Section: Discussionmentioning
confidence: 99%
“…The initial pool of 83 variables was filtered through information gain (IG) and chi‐squared (χ 2 ) feature selection techniques. Only those variables with nonzero IG and nonzero χ 2 values were selected for further investigation (Banerjee, Chua, & Kim, ; Forman, ; O'Mahony & Smyth, )…”
Section: Linguistic Studymentioning
confidence: 99%
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