Detecting the Hate Code on Social Media

• Main Authors: Magu, Rijul, Joshi, Kshitij, Luo, Jiebo
• Format: Journal Article
• Language: English
• Published: 15-03-2017
• Subjects: Computer Science - Social and Information Networks
• DOI: 10.48550/arxiv.1703.05443

Eleventh International AAAI Conference on Weblogs and Social
Media., 2017, 608-612 Social media has become an indispensable part of the everyday lives of
millions of people around the world. It provides a platform for expressing
opinions and beliefs, communicated to a massive audience. However, this ease
with which people can express themselves has also allowed for the large scale
spread of propaganda and hate speech. To prevent violating the abuse policies
of social media platforms and also to avoid detection by automatic systems like
Google's Conversation AI, racists have begun to use a code (a movement termed
Operation Google). This involves substituting references to communities by
benign words that seem out of context, in hate filled posts or Tweets. For
example, users have used the words Googles and Bings to represent the
African-American and Asian communities, respectively. By generating the list of
users who post such content, we move a step forward from classifying tweets by
allowing us to study the usage pattern of these concentrated set of users.