The language used in online content often plays on people's reactions like outrage and fear, not necessarily because people seek it, but because these emotions work on them. People may not actively look for such content but are drawn to it nonetheless. Algorithms in social media platforms like YouTube and Twitter are designed to engage users, leading to personalized content recommendations. Personal preferences, like watching entertainment videos, may limit exposure to problematic algorithms. However, platforms like YouTube are not focused on fostering a shared reality among users. Organizations like More In Common have developed metrics to gauge Perception Gaps and address societal polarization influenced by algorithm-driven content consumption.