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The proliferation of harmful content on online platforms is a major societalproblem, which comes in many different forms including hate speech, offensivelanguage, bullying and harassment, misinformation, spam, violence, graphiccontent, sexual abuse, self harm, and many other. Online platforms seek tomoderate such content to limit societal harm, to comply with legislation, andto create a more inclusive environment for their users. Researchers havedeveloped different methods for automatically detecting harmful content, oftenfocusing on specific sub-problems or on narrow communities, as what isconsidered harmful often depends on the platform and on the context. We arguethat there is currently a dichotomy between what types of harmful contentonline platforms seek to curb, and what research efforts there are toautomatically detect such content. We thus survey existing methods as well ascontent moderation policies by online platforms in this light and we suggestdirections for future work.

Detecting Harmful Content On Online Platforms: What Platforms Need Vs. Where Research Efforts Go