docs: def compute_log_degrees(brands, exemplars):
      """ For each follower, let Z be the total number of brands they follow.
      Return a dictionary of 1. / log(Z), for each follower.
      """
      counts = Counter()
      for followers in brands.values():  # + exemplars.values():  # Include exemplars in these counts? No, don't want to penalize people who follow many exemplars.
          counts.update(followers)
      counts.update(counts.keys())  # Add 1 to each count.
      for k in counts:
          counts[k] = 1. / math.log(counts[k])
      return counts