polarity classification 0.002154874
metaphor polarity 0.002014609
polarity task 0.001958856
negative polarity 0.0018562600000000002
positive polarity 0.001753151
polarity liwc 0.001716644
polarity class 0.001703365
polarity identification 0.001669233
polarity classes 0.0016357540000000001
corresponding polarity 0.001632602
affect polarity 0.0016228990000000001
polarity labels 0.0015958790000000001
polarity clas 0.001566752
ative polarity 0.001558381
fect polarity 0.001551457
language com 0.001507439
accuracy model 0.0014654639999999999
regression model 0.001452783
same features 0.001447301
prediction model 0.00143521
different feature 0.001419572
classification task 0.00141847
polarity 0.00134763
different information 0.001346271
such information 0.001336346
liwc features 0.001327354
affect model 0.001318699
word categories 0.001298749
sion model 0.001283411
information source 0.001262116
gression model 0.001249248
language 0.00123778
contextual features 0.001232969
classification accuracy 0.001229278
such models 0.001213774
different languages 0.001177563
gram features 0.001176431
feature set 0.00117081
classification problem 0.001164689
word lists 0.001148811
word count 0.0011432249999999999
trigger word 0.001140254
lexical information 0.001130434
random feature 0.00112748
classification function 0.001123814
data annotation 0.001114452
classification figure 0.001108388
classification tasks 0.001096442
annotated data 0.001085127
metaphor texts 0.001059103
model 0.00104343
classification algorithms 0.001033991
different machine 0.001030029
regression task 0.001020579
different lan 0.001018154
target information 0.001002097
valence task 9.90293E-4
different classes 9.88829E-4
metaphor identification 9.88582E-4
information sources 9.764929999999999E-4
different fea 9.67155E-4
metaphor example 9.622000000000001E-4
features 9.5834E-4
feature sets 9.526269999999999E-4
analysis task 9.442879999999999E-4
different triggers 9.39619E-4
regression models 9.32347E-4
ical information 9.29877E-4
positive english 9.1861E-4
prediction models 9.14774E-4
different views 9.079400000000001E-4
mse metaphor 9.06869E-4
such informa 9.06469E-4
english texts 9.05213E-4
only information 8.98432E-4
fscore metaphor 8.976260000000001E-4
multilingual metaphor 8.97566E-4
majority classifier 8.96869E-4
such intensity 8.96667E-4
farsi metaphor 8.89749E-4
novel corpus 8.88375E-4
novel task 8.83956E-4
metaphor polar 8.83539E-4
concrete metaphor 8.821660000000001E-4
combined metaphor 8.737390000000001E-4
metaphor detection 8.71573E-4
sentiment analysis 8.713010000000001E-4
present source 8.688260000000001E-4
negative class 8.64365E-4
target domain 8.59087E-4
individual information 8.57014E-4
computational models 8.5695E-4
vidual information 8.53981E-4
information gain 8.52482E-4
training algorithm 8.47723E-4
training error 8.472E-4
positive score 8.416960000000001E-4
task definition 8.38994E-4
automatic models 8.384110000000001E-4
ity task 8.351999999999999E-4
