Detecting Hate Speech on Social Media to Prevent Violence

Looking at the history of mankind spanning thousands of years, hatred was always present and people have been persecuted for a wide variety of reasons up until this day, but in recent times hate has been digitized and weaponized with the rise of social media. One of the biggest roadblocks law enforcement agencies and private institutions face when attempting to detect then combat hateful material found on social networks, especially Twitter, is how exactly to deal with the massive amount of data, including tons of false positives, sarcastic posts, emerging trends that go viral within hours as well as many other variables. It's a monumental task that no analyst, army of analysts or social media intelligence tools of the past can accomplish. For the past 2 years, the team at Soteria Intelligence has focused on developing technologies to confront online hate, school threats, terrorist propaganda and other challenges we face in a very unorthodox way, and through our research and development it became clear that the only way to solve the complex problem at hand was to use deep learning and machine learning. Taking 10 years of research on social media behavior and 5 years of research on social media threats in particular, along with input from a wide range of subject-matter experts, we've focused on creating machine learning systems with ability to assess social media activity faster and more accurately than humanly possible.