something most people worry about and try to protect, but on social networking
giants like Facebook, it’s almost impossible to protect all of your information despite
privacy settings. Now, the New York Police Department (NYPD) is data mining
Facebook, Twitter and MySpace to track hooligans who have committed or are
planning to commit crimes.
O’Connor, 23, assistant commissioner for the NYPD who is an online drug and
gang expert, is now the head of a new juvenile justice unit. The new unit will
operate under the Community Affairs Bureau and include outreach programs.
Known for his
successful tactics of "online
policing," which has
nabbed criminals such as sexual predators trying to meet children on the internet,
O’Connor and his staff will be using the Web in this particular unit as well.
They plan to mine social media sites like Facebook, Twitter and MySpace in
order to find criminals bragging about a crime they've committed or planning to
commit a crime.
has already proved to be successful. O'Connor successfully provided information
on a number of shooting cases thanks to social networking. Also, the NYPD has
caught other criminals who've bragged about their illegal activities online,
such as Calvin Pietri, who killed Anthony Collao in an anti-gay attack at
Woodhaven, Queens. Another Internet-related case consisted of a Facebook feud
between Kayla Henriques and Kamisha Richards over a $20 loan for diapers, which
ended in Richards' death. Henriques was a suspect due to the Facebook fight.
New York isn't
the only city with positive results from data mining social networks. London's
rioters and looters have used Twitter and BlackBerry messages this week to
choose targets to burn or loot. Police have been able to use the social
networks to find pictures of these criminals.
The NYPD plans
to use online policing to find info about gang showdowns, murder cases,
problematic house parties and other forms of commotion. While it could be
helpful in certain cases, as always, there is potential
for abuse if a police officer
were to misinterpret something on a social network.