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negative sentiment 0.0034523670000000005
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general sentiment 0.003185998
sentiment detection 0.0031441240000000003
multimodal sentiment 0.003136003
sentiment annotations 0.003099473
sentiment annotation 0.003062074
act sentiment 0.003053665
sentiment clas 0.003029911
sentiment classi 0.003027592
sentiment classifiers 0.003011843
sentiment identification 0.003004815
dominant sentiment 0.0029796840000000002
tracking sentiment 0.0029793050000000002
sentiment timelines 0.002975806
citation sentiment 0.002975806
sentiment 0.00274943
linguistic features 0.002043052
visual features 0.001794554
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facial features 0.0017608020000000001
energy features 0.0017397600000000001
unigram features 0.001733447
loudness features 0.001695944
acoustic features 0.001676454
individual features 0.001674053
spectral features 0.0016518510000000002
informative features 0.0016489550000000001
cepstral features 0.00164627
prosody features 0.001639856
feature vector 0.001531693
analysis model 0.001494396
feature analysis 0.0014580259999999999
features 0.00140079
textual data 0.001339019
multimodal feature 0.001337535
opinion words 0.001319219
feature vectors 0.001251619
single feature 0.001248037
training set 0.0012394630000000001
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feature weights 0.001216038
feature extraction 0.001215836
opinion classification 0.001215472
linguistic classifier 0.0012029929999999999
smile feature 0.001201147
negative utterances 0.001191591
speech frame 0.001160664
video set 0.0011001750000000001
text reviews 0.001097536
speech signal 0.001076345
text analysis 0.001074209
speech cues 0.00107322
speech stream 0.001067571
speech formants 0.001064286
speech sig 0.001064286
classification experiments 0.001063168
previous work 0.0010196559999999999
opinion analysis 0.0010084550000000001
opinion utterances 9.900450000000002E-4
model 9.87332E-4
video reviews 9.69936E-4
negative opinions 9.690230000000001E-4
other modalities 9.6864E-4
negative state 9.667580000000001E-4
negative comments 9.657540000000001E-4
other media 9.58357E-4
previous utterance 9.552440000000001E-4
feature 9.50962E-4
utterances dataset 9.460170000000001E-4
representative set 9.41884E-4
svm classifier 9.39219E-4
other datasets 9.2872E-4
linguistic modalities 9.282979999999999E-4
accuracy baseline 9.25746E-4
analysis approach 9.19771E-4
broad domain 9.0925E-4
same speaker 9.08281E-4
linguistic datastreams 9.07679E-4
development set 9.073480000000001E-4
entire set 8.9996E-4
audio classifier 8.968069999999999E-4
large dataset 8.928930000000001E-4
different types 8.898739999999999E-4
multimodal opinion 8.87964E-4
product reviews 8.85801E-4
visual information 8.81011E-4
annotated utterances 8.79836E-4
news articles 8.75794E-4
linguistic datastream 8.70002E-4
traditional text 8.60937E-4
same type 8.58775E-4
further analysis 8.56427E-4
analysis experiments 8.56151E-4
ment analysis 8.48262E-4
multimodal dataset 8.43936E-4
text modality 8.43888E-4
speech 8.35191E-4
good agreement 8.324459999999999E-4
