New research can identify extremists online, even before they post dangerous content | 9/12/2018 | Staff
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New research has found a way to identify extremists, such as those associated with the terrorist group ISIS, by monitoring their social media accounts, and can identify them even before they post threatening content.

The number and size of online extremist groups using social networks to harass users, recruit new members, and incite violence is rapidly increasing. While social media platforms are working to combat this (in 2016, Twitter reported it had shut down 360,000 ISIS accounts) they traditionally rely heavily on users' reports to identify these accounts.

Addition - Account - User - Account - Accounts

In addition, once an account has been suspended, there is little that can be done to prevent a user from opening up a new account, or multiple accounts.

"Social media has become a powerful platform for extremist groups, ranging from ISIS to white nationalist "alt-right" groups," said Zaman. "These groups use social networks to spread hateful propaganda and incite violence and terror attacks, making them a threat to the general public."

Researchers - Twitter - Data - Seed - Users

The researchers collected Twitter data from approximately 5,000 "seed" users who were either known ISIS members or who were connected to many known ISIS members as friends or followers. They obtained their names through news stories, blogs, and reports released by law enforcement agencies and think tanks.

In addition to reviewing the content of 4.8 million tweets from these users' timelines (including text, links, hash tags, and mentions), they also tracked account suspensions, as well as any suspensions of their friends and followers accounts.

Purpose - Study - Researchers - Account - Networks

For the purpose of this study, the researchers focused on the account networks forged by known ISIS and Al Qaeda sympathizers and known foreign fighters and content that had been flagged by Twitter as terrorist in nature.

Using statistical modeling...
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