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different word 0.002477334
other words 0.002234527
negative words 0.002225586
negative word 0.002155916
negative sentiment 0.002132546
sentiment analysis 0.002132161
word features 0.0020899919999999997
sentiment lexicon 0.00206993
positive words 0.00206813
general sentiment 0.002009464
positive word 0.00199846
word class 0.001987142
sentiment values 0.001961812
important words 0.0019372559999999998
sentiment score 0.0019249669999999999
sentiment dictionary 0.0019240289999999998
tive words 0.0018866959999999998
neutral words 0.001886638
important word 0.0018675859999999999
words representation 0.0018510389999999999
polarity classification 0.001826658
word con 0.001822836
negative polarity 0.001822366
specific word 0.0018063749999999998
word level 0.0018031739999999998
itive words 0.0018027219999999999
strongsubj words 0.0018024909999999998
word category 0.0017887579999999999
word representation 0.0017813689999999999
sentiment orientation 0.0017770059999999998
word categories 0.001774534
individual word 0.0017654989999999998
frequent word 0.001763531
word clas 0.0017555539999999999
word combinations 0.0017502519999999999
word connections 0.001737537
word classifica 0.001730084
word combina 0.001729661
sentiment dictionaries 0.001705863
sentiment analyses 0.0017052229999999999
words 0.00157458
different features 0.0015575060000000002
prior polarity 0.001498815
work opinion 0.001492103
sentiment 0.00148154
polarity items 0.001467016
different edges 0.001463856
contextual polarity 0.00142064
polarity modification 0.001416889
polarity shifters 0.001395276
graph model 0.001393165
different tonality 0.001368796
different opinions 0.0013527930000000001
different statements 0.00132318
opinion mining 0.001307975
graph nodes 0.001306536
possible graph 0.001297067
sentence features 0.001254235
different input 0.001249894
different datasets 0.001248735
first sentence 0.0012481850000000002
same time 0.0012425560000000001
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same class 0.001229421
opinion observer 0.001222411
different parts 0.001218033
different topics 0.001216139
negative news 0.001216039
automated opinion 0.001211042
different kinds 0.00121045
opinion ori 0.0012084880000000002
actual opinion 0.001206952
different tonal 0.00120685
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second method 0.001201273
different tonalities 0.001199908
different viewpoints 0.001199908
different corpora 0.001198847
different contributions 0.001197085
other type 0.00119508
classification approach 0.0011939659999999999
polarity 0.00117136
connected graph 0.001157868
same tonality 0.001143561
complete graph 0.0011417390000000001
same scores 0.001118922
type information 0.0011027279999999999
same function 0.001101124
same statements 0.001097945
results table 0.001074807
features values 0.0010653540000000001
news domain 0.001060444
tonality classification 0.00105167
same sen 0.001038507
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same category 0.001031037
negative state 0.0010109469999999999
negative statements 0.001001762
same size 9.99802E-4
