sentiment word 0.00434571
negative sentiment 0.00418096
sentiment words 0.004074582
positive sentiment 0.004026096
sentiment phrases 0.0038422599999999997
sentiment phrase 0.003723858
sentiment lexicon 0.0035388859999999998
tive sentiment 0.003457857
candidate sentiment 0.003421938
ative sentiment 0.003409392
sentiment terms 0.0033949139999999997
sentiment candidates 0.0033852459999999997
itive sentiment 0.003373808
sentiment term 0.0033532569999999997
afinn sentiment 0.003351528
correlated sentiment 0.003351528
sentiment 0.00312586
data set 0.001650258
following word 0.001606758
seed word 0.001507168
positive polarity 0.0014970790000000001
evaluation data 0.001483804
negative values 0.001482273
fixed word 0.001451871
word dictionaries 0.001451075
negative situation 0.001426112
negative opinion 0.001395773
positive values 0.0013274089999999999
negative activities 0.001317469
bootstrapping data 0.001310601
negative activity 0.001303824
negative situations 0.001295451
negative instances 0.00128715
negative situa 0.001281833
negative emotions 0.001280624
positive situation 0.001271248
dard data 0.001264816
multiple tweets 0.0012470860000000001
new tweets 0.001224255
sarcastic tweets 0.001220323
syntactic features 0.001212549
positive sen 0.001202956
subjective words 0.001200887
positive sentiments 0.001192545
positive predicative 0.001180595
additional tweets 0.001178434
tic tweets 0.001167085
annotated tweets 0.001163968
positive senti 0.0011582229999999999
sarcasm classification 0.001149949
positive examples 0.001138279
positive verb 0.001132593
positive instances 0.001132286
same set 0.001132092
unigram features 0.00111725
dutch tweets 0.001090435
situation phrases 0.0010874119999999998
speech features 0.001080007
sarcastic tweet 0.001078754
new phrases 0.001076846
prior tweet 0.001071727
gram features 0.001068784
twitter con 0.00106628
previous tweet 0.001062729
igram features 0.0010580960000000001
negative 0.0010551
large set 0.0010527330000000001
related work 0.001037441
candidate phrases 0.001012478
noun phrases 0.0010121219999999998
phrases seed 0.001003718
single tweet 9.99512E-4
predicative phrases 9.967589999999998E-4
tweet collection 9.85858E-4
timent phrases 9.80728E-4
pos patterns 9.78532E-4
nominal phrases 9.73223E-4
situation phrase 9.6901E-4
opinionfinder system 9.68467E-4
sarcasm label 9.526550000000001E-4
other candidates 9.50912E-4
verb phrases 9.487569999999999E-4
words 9.48722E-4
date phrases 9.44299E-4
ation phrases 9.43442E-4
other keyboard 9.42828E-4
uation phrases 9.42328E-4
vector machine 9.35968E-4
tive polarity 9.2884E-4
previous work 9.24613E-4
sarcasm corpus 9.233070000000001E-4
strong polarity 9.21576E-4
phrase structures 9.1948E-4
phrase list 9.05632E-4
ment phrase 9.00137E-4
opposite polarity 8.99852E-4
support vector 8.97429E-4
candidate phrase 8.940759999999999E-4
noun phrase 8.9372E-4
linguistic expressions 8.915120000000001E-4
