Whilst crime in general has been falling for decades, hate crime has gone in the other direction. Especially after the US election 2016, it has risen to a new level against minorities- colored people, muslims, jews, LGBT community. The perpetrators often share their threats blatantly before committing the crime. If we can figure out the credible threats by automatically analyzing the text patterns, then we can save lives. In this project, we will decompose the overall detection problem into detection of sensitive topics, lending itself into text classification sub-problems. We will scrape data from social microblogs to build our corpus and then we will experiment with different classifiers.



Nayeem Aquib


  • Philipp Heinrich
  • Peter Uhrig
  • Francis Steen
  • Kai Chan