features sentiment 0.002407572
sentiment classification 0.002296952
sentiment detection 0.0021602319999999998
sentiment analysis 0.002113286
related tweets 0.002092503
relevant tweets 0.002084236
similar tweets 0.002025914
sentiment label 0.002020335
sentiment labels 0.001976934
short tweets 0.001963755
processing tweets 0.001933405
statistical sentiment 0.001894054
sentiment lexicons 0.001883187
neutral sentiment 0.001872798
ferent sentiment 0.001861098
sentiment dictio 0.001857971
new information 0.001767338
tweets 0.00167205
sentiment 0.00164471
tweet vector 0.001549063
new features 0.00144637
first words 0.001426412
share information 0.0013849140000000001
information source 0.001380631
analysis system 0.001359204
training data 0.001358839
complement information 0.001298906
word normalization 0.0012619600000000001
word matching 0.001246569
test data 0.001240178
media news 0.001239843
modifier word 0.001226681
syntactic features 0.00121528
same news 0.001198462
other events 0.001198335
such words 0.001164057
monitoring system 0.0011544419999999999
social media 0.001130842
topic labeling 0.001128426
training set 0.001116216
sis system 0.001107343
tweet 0.00109358
main news 0.0010915060000000001
information 0.00108383
data mining 0.001075879
particular twitter 0.0010732979999999999
experiments data 0.00104775
twitter api 0.001047127
ing content 0.001034384
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important news 0.001030578
weka data 0.001027706
semantic features 0.00102591
first step 0.001024603
online news 0.001008223
training models 9.86937E-4
different categories 9.84121E-4
different crisis 9.800359999999999E-4
boolean features 9.77671E-4
crisis events 9.77515E-4
related work 9.74935E-4
other approaches 9.66448E-4
news clusters 9.53457E-4
certain events 9.484490000000001E-4
news monitoring 9.477590000000001E-4
news cluster 9.44487E-4
linking news 9.3812E-4
new articles 9.36311E-4
news sites 9.277510000000001E-4
same approach 9.277210000000001E-4
high negative 9.26339E-4
search query 9.2633E-4
news story 9.243060000000001E-4
other users 9.24018E-4
classification module 9.212300000000001E-4
vector similarity 9.209940000000001E-4
future events 9.081410000000001E-4
mainstream news 9.06076E-4
news stories 9.04512E-4
ferent news 9.00333E-4
news items 8.986910000000001E-4
emm news 8.986910000000001E-4
nancial news 8.986910000000001E-4
system 8.90628E-4
event 8.86231E-4
language analysis 8.78612E-4
different datasets 8.7371E-4
tary content 8.70388E-4
related research 8.67349E-4
development set 8.63103E-4
different levels 8.41762E-4
future work 8.38791E-4
little work 8.38119E-4
high positive 8.308040000000001E-4
media monitoring 8.19712E-4
twitter 8.1896E-4
related approaches 8.12398E-4
additional training 8.117879999999999E-4
learning process 8.114039999999999E-4
negative feelings 8.056480000000001E-4
