Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28713880
&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215
Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\28713880
.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117 Proc+IEEE+ACM+Int+Conf+Adv+Soc+Netw+Anal+Min
2016 ; 206
(ä): 685-692
Nephropedia Template TP
gab.com Text
Twit Text FOAVip
Twit Text #
English Wikipedia
Finding Street Gang Members on Twitter
#MMPMID28713880
Balasuriya L
; Wijeratne S
; Doran D
; Sheth A
Proc IEEE ACM Int Conf Adv Soc Netw Anal Min
2016[Aug]; 206
(ä): 685-692
PMID28713880
show ga
Most street gang members use Twitter to intimidate others, to present outrageous
images and statements to the world, and to share recent illegal activities. Their
tweets may thus be useful to law enforcement agencies to discover clues about
recent crimes or to anticipate ones that may occur. Finding these posts, however,
requires a method to discover gang member Twitter profiles. This is a challenging
task since gang members represent a very small population of the 320 million
Twitter users. This paper studies the problem of automatically finding gang
members on Twitter. It outlines a process to curate one of the largest sets of
verifiable gang member profiles that have ever been studied. A review of these
profiles establishes differences in the language, images, YouTube links, and
emojis gang members use compared to the rest of the Twitter population. Features
from this review are used to train a series of supervised classifiers. Our
classifier achieves a promising F(1) score with a low false positive rate.