
    In a social media content recommendation system, determine the influence factor at position n in the user interaction sequence, where each number represents how many previous user interactions should be considered for the current content suggestion, following the pattern where each influence factor equals the sum of the numbers at positions given by the previous two influence factors. The sequence starts with 1,1 and each subsequent number follows this recursive pattern.
    

    
def sequence(n):
    """
    In a social media content recommendation system, determine the influence factor at position n in the user interaction sequence, where each number represents how many previous user interactions should be considered for the current content suggestion, following the pattern where each influence factor equals the sum of the numbers at positions given by the previous two influence factors. The sequence starts with 1,1 and each subsequent number follows this recursive pattern.
    

    """
def sequence(n):
    """
    In a social media content recommendation system, determine the influence factor at position n in the user interaction sequence, where each number represents how many previous user interactions should be considered for the current content suggestion, following the pattern where each influence factor equals the sum of the numbers at positions given by the previous two influence factors. The sequence starts with 1,1 and each subsequent number follows this recursive pattern.
    

    """
    if n == 1 or n == 2:
        return 1
    else:
        return sequence(sequence(n - 1)) + sequence(n - sequence(n - 1))