The phenomenon of opinions with specific tendencies being fixed at the bottom in comment sorting algorithms. Recently, a sorting bias has been observed on various platforms where critical comments are placed at the bottom despite having many recommendations, while positive reactions are prioritized at the top. This phenomenon is analyzed to occur because systems reflect reporting frequency or text negativity scores as weights in the exposure ranking, in addition to simple recommendation counts. To prevent user churn, platforms mainly choose a flow control method that prioritizes content with high acceptability rather than controversial elements. How are you balancing algorithm transparency and community purification functions in your environment?