sentiment classification 0.001761943
vector model 0.0016987579999999999
other words 0.001686424
structural model 0.001635077
negative sentiment 0.00158378
simple model 0.001569774
training data 0.001568957
struct model 0.001524868
sentiment task 0.001518116
review data 0.001507605
model parameters 0.001503312
syntactic tree 0.001493022
same tree 0.0014898070000000001
joint model 0.00148026
fvec model 0.0014795099999999999
sentiment classifier 0.001475806
model scales 0.00146873
model adaptability 0.0014553169999999998
same feature 0.00145458
sentiment research 0.0014534069999999999
model misclassifies 0.0014523169999999998
syntactic features 0.001443983
comments data 0.0014435009999999998
context words 0.001416648
previous sentiment 0.0014136980000000001
semantic models 0.00139777
tion words 0.001394963
test sentiment 0.001391947
tree kernel 0.001391284
polarity words 0.001380456
tree nodes 0.001376829
sentiment analysis 0.00137169
negation words 0.0013691889999999998
comment sentiment 0.001368704
negative word 0.0013344540000000001
different product 0.001330099
sentiment lexicon 0.0013254529999999999
sentiment prediction 0.001319413
classification accuracy 0.001319336
target data 0.001318244
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ing data 0.001301463
cept words 0.001297134
matched words 0.001297134
ambiguous sentiment 0.001296922
sentiment lexi 0.001286128
data distribution 0.001286106
fvec sentiment 0.00127966
neutral sentiment 0.001269232
description sentiment 0.001259836
sentiment lexicons 0.001253564
youtube data 0.0012520769999999999
lexical nodes 0.001242714
model 0.00123914
feature vector 0.001221972
tree structures 0.001219951
classification task 0.001201479
different domains 0.001193282
noisy data 0.001192185
high classification 0.0011888559999999999
little data 0.0011839189999999999
different youtube 0.0011831440000000001
dependency tree 0.001182034
classification system 0.00118189
language processing 0.0011791190000000002
tree structure 0.001177364
data sparsity 0.0011716209999999999
vector models 0.00116723
tree kernels 0.001159957
structural feature 0.001158291
standard feature 0.001145915
structural features 0.0011444790000000001
ral language 0.00114379
structural information 0.001134639
shallow tree 0.001131435
different quality 0.0011287089999999999
training set 0.001125667
different types 0.001125064
word distribution 0.001122567
baseline feature 0.001119335
syntactic structures 0.001117811
tree fragments 0.001109685
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topic product 0.001109026
different properties 0.001108255
feature space 0.001107282
feature vectors 0.001105827
structural models 0.0011035490000000001
different levels 0.001102549
different polarities 0.001099987
syntactic trees 0.001099277
word xoom 0.001093464
tree representation 0.001089381
same domain 0.001088755
type classification 0.001086075
following feature 0.00108584
strong feature 0.001085733
words 0.00108319
similarity kernel 0.001079391
tree level 0.001078532
