A social media platform is experiencing a new form of harassment where automated systems generate thousands of unique, subtly negative comments targeting specific individuals. These comments are contextually relevant and varied enough to bypass traditional keyword-based filters. The platform's safety team proposes implementing a new system that analyzes the linguistic style, posting frequency, and network patterns of comments to detect and block those likely generated by automated tools. Based on this scenario, evaluate the primary strength and a significant potential weakness of this proposed countermeasure.