A Review of Standard Text Classification Practices for Multi-label Toxicity Identification of Online Content

WS 2018 Isuru GunasekaraIsar Nejadgholi

Language toxicity identification presents a gray area in the ethical debate surrounding freedom of speech and censorship. Today{'}s social media landscape is littered with unfiltered content that can be anywhere from slightly abusive to hate inducing... (read more)

PDF Abstract

Code


No code implementations yet. Submit your code now

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper