deceptive reviews 0.002543586
online reviews 0.002417443
deceptive review 0.002397666
good reviews 0.002390371
hotel reviews 0.00236888
truthful reviews 0.002325443
positive reviews 0.002323189
restaurant reviews 0.002297217
review text 0.002292425
hotel review 0.00222296
fake reviews 0.002186243
employee reviews 0.002179947
reference reviews 0.002164068
customer reviews 0.002140411
doctor reviews 0.002134691
expert reviews 0.00213422
ceptive reviews 0.002127895
fictitious reviews 0.002122196
reviews accord 0.002119312
glowing reviews 0.002117298
general features 0.002019285
reviews 0.00186553
pos features 0.001760644
such feature 0.001734518
review 0.00171961
syntactic features 0.001699962
textual features 0.0016910900000000001
deceptive opinion 0.0016517749999999999
standard opinion 0.0016205199999999999
unigram features 0.001596594
guistic features 0.001589717
other topic 0.001567767
other words 0.001559655
opinion problem 0.0015186829999999998
opinion spam 0.001465077
data set 0.001342895
features 0.00133694
feature sets 0.001310686
unigram feature 0.001273824
same product 0.001270177
tive opinion 0.0012685729999999998
ceptive opinion 0.001236084
general classifier 0.0012252230000000001
following distribution 0.001223223
classification task 0.001215483
standard dataset 0.0012054309999999999
classification results 0.001200892
other domains 0.001185817
deceptive hotel 0.0011814059999999999
different sources 0.001174249
general cues 0.001168204
generative model 0.001166657
training data 0.001164742
other lin 0.001152861
other cities 0.001147601
other derivatives 0.001147601
additive model 0.001143977
labeled data 0.0011322440000000001
deceptive restaurant 0.001109743
topic models 0.00110272
sage model 0.001102705
data annotation 0.001070789
data creation 0.001065609
learning approaches 0.001062636
data acquisition 0.0010558780000000001
classifier performance 0.001052419
negative ones 0.001048062
svm performance 0.0010456139999999998
online deception 0.001041133
different domains 0.001039684
different classes 0.0010374540000000002
good performance 0.001034382
different facets 0.001022253
generative approach 0.0010179149999999999
different types 0.001016432
feature 0.00101417
general difference 0.001006807
posterior distribution 0.001006626
bayesian approach 0.001006623
same domain 9.964729999999999E-4
text collection 9.88548E-4
human readers 9.82815E-4
gold standard 9.7999E-4
general rule 9.75388E-4
deception cues 9.75079E-4
work spam 9.74124E-4
opinion 9.73719E-4
human annotators 9.72685E-4
general population 9.655029999999999E-4
negative emotion 9.636499999999999E-4
truthful hotel 9.63263E-4
experimental results 9.620900000000001E-4
deceptive opin 9.614770000000001E-4
negative expert 9.59185E-4
spam detection 9.53466E-4
hotel domain 9.53393E-4
human intelligence 9.50812E-4
general concepts 9.49859E-4
related work 9.485819999999999E-4
standard machine 9.43139E-4
