Now no one could be spared for using abusive language on Twitter. In a first of its kind development, a team from the International Institute of Information Technology, Hyderabad, (IIIT-H) has come up with a system to detect ‘hate speech’ on microblogging site Twitter. The research was conducted at the IIIT-H’s Informational and Retrieval Extraction Lab (IREL) by using natural language processing, semantics and artificial intelligence.
The team of four members was working on the topic of ‘deep learning for hate speech’ on micro-blogging site Twitter for close to a year.
The team includes Vasudeva Varma, Professor and Dean (R&D) at IIIT-H, students Pinkesh Badjatiya and Shashank Gupta, and adjunct faculty Manish Gupta.
According to the team members, the system can detect abusive language, sexist and racist speech and flag offensive content.
This is useful in filtering abusive, hateful content, and also analyzing public sentiment to get to the root of the problem.
Team member Vasudev Varma said to detect hate speech, a popular approach called supervised learning is used.
Essentially a computer algorithm is fed many examples of text from each form of hate, which can be categorised as ‘racist’ or ‘sexist’ tweets. The algorithm is designed in such a way that it learns as it sees the data, and after the algorithm terminates, the programme is smart enough to recognise racism or sexism in a text.”