Find –In the World Its Automated detection of doxing on Twitter with over 96% accuracy it !

A new automated approach to detect doxing—a form of cyberbullying in which certain private or personally identifiable information is publicly shared without an individual’s consent or knowledge—may help social media platforms better protect their users, according to researchers from Penn State’s College of Information Sciences and Technology.

The research on doxing could lead to more immediate flagging and removal of sensitive personal information that has been shared without the owner’s authorization. To date, the research team has only studied Twitter, where their novel proposed approach uses machine learning to differentiate which tweet containing personally identifiable information is maliciously shared rather than self-disclosed.

They have identified an approach that was able to automatically detect doxing on Twitter with over 96% accuracy, which could help the platform—and eventually other social media platforms—more quickly and easily identify true cases of doxing.

“The focus is to identify cases where people collect sensitive personal information about others and publicly disclose it as a way of scaring, defaming, threatening or silencing them,” said Younes Karimi, doctoral candidate and lead author on the paper. “This is dangerous because once this information is posted, it can quickly be shared with many people and even go beyond Twitter. The person to whom the information belongs needs to be protected.”