As technology widens our possibilities for communication and knowledge discovery, it can also leave us vulnerable to misinformation and toxic, abusive, manipulative content, which can cause substantial harm both individually and collectively. Combating the malicious use of social media implies solving very complex and subjective tasks that require a synergy between automated tools and humans. Existing ML models, trained on vast datasets, excel in many tasks like summarization, translation, and human-like content generation. However, we argue that in order for those tools to be effective, they need to be able to form the types of representations and semantic inferences that humans use and create, have the ability to combine automatically acquired data and insights with the domain-specific expertise of the users, and involve high-level reasoning, all three features in which knowledge-based and symbolic approaches to artificial intelligence seem to be well-fitted for.