
    Design a function for a social media recommendation algorithm that calculates the total influence score by summing the squared weights of the n most significant user engagement types, where engagement weights are represented by consecutive odd numbers. The resulting score will be used to determine the strength of content recommendations based on user interaction patterns.
    

    
def square_Sum(n):
    """
    Design a function for a social media recommendation algorithm that calculates the total influence score by summing the squared weights of the n most significant user engagement types, where engagement weights are represented by consecutive odd numbers. The resulting score will be used to determine the strength of content recommendations based on user interaction patterns.
    

    """
def square_Sum(n):
    """
    Design a function for a social media recommendation algorithm that calculates the total influence score by summing the squared weights of the n most significant user engagement types, where engagement weights are represented by consecutive odd numbers. The resulting score will be used to determine the strength of content recommendations based on user interaction patterns.
    

    """
    return int(n * (4 * n * n - 1) / 3)