age gender 0.002858115
gender models 0.0026311200000000002
gender model 0.002599099
gender prediction 0.00247014
other features 0.0024673919999999997
gender groups 0.00245378
gender lexica 0.002410998
gender predictions 0.002370533
gender informa 0.002365355
infers gender 0.002360035
gender 0.00214663
media language 0.0017253619999999998
user data 0.001633067
features 0.00161445
twitter data 0.0015845759999999999
language usage 0.00155492
primary language 0.0014839179999999999
native language 0.001447681
media data 0.0014464489999999998
such work 0.0014136880000000002
training data 0.001377834
additional data 0.001282957
single word 0.001280772
word usage 0.001274259
available data 0.001254379
language 0.00122595
facebook data 0.001220039
total word 0.0012109619999999999
word lexica 0.001209657
primary data 0.0012050049999999999
classification models 0.001199024
word count 0.001185123
twitter users 0.001181794
weighted word 0.001167542
book data 0.001167397
vector classification 0.0011643369999999999
social media 0.001149476
other domains 0.001123473
other approaches 0.001107508
other settings 0.001093099
other situations 0.001081156
random twitter 0.001071963
twitter dataset 0.001070598
age prediction 0.001034995
words 0.00101391
work online 0.001011359
certain age 0.001001976
test set 9.91231E-4
feature coeffi 9.84509E-4
formative feature 9.84509E-4
age group 9.83968E-4
average user 9.83017E-4
twitter sample 9.73827E-4
mean age 9.66393E-4
online media 9.462139999999999E-4
based age 9.40016E-4
age predictions 9.35388E-4
many studies 9.33E-4
social science 9.325550000000001E-4
distribution age 9.313279999999999E-4
age bins 9.21913E-4
media sentiment 9.085549999999999E-4
user decreases 9.00651E-4
random set 8.946939999999999E-4
previous results 8.89452E-4
large set 8.88759E-4
additional users 8.80175E-4
high accuracy 8.795699999999999E-4
profile information 8.791690000000001E-4
sentiment lexicon 8.76859E-4
social questions 8.7152E-4
related work 8.695160000000001E-4
test sample 8.672490000000001E-4
reasonable accuracy 8.67052E-4
many coefficients 8.64056E-4
social sciences 8.6365E-4
social sci 8.60444E-4
many aspects 8.45088E-4
accuracy burger 8.392619999999999E-4
future work 8.36192E-4
media studies 8.2245E-4
many ques 8.222920000000001E-4
male bias 8.187260000000001E-4
facebook users 8.17257E-4
media content 8.119469999999999E-4
facebook test 8.03963E-4
total number 7.91152E-4
annotated users 7.90699E-4
sentiment analysis 7.89697E-4
lexical representations 7.890039999999999E-4
primary test 7.889290000000001E-4
current work 7.88009E-4
blogger test 7.851500000000001E-4
linear kernel 7.84637E-4
top system 7.80736E-4
work infers 7.779620000000001E-4
work preferences 7.777600000000001E-4
main test 7.77627E-4
feature 7.72846E-4
sify users 7.71256E-4
