Compute a score for each follower that is sum_i (1/n_i), where n_i is
    the degree of the ith exemplar they follow.
    >>> compute_rarity_scores({'e1':{1,2,3,4}, 'e2':{4,5}}).items()
    [(1, 0.25), (2, 0.25), (3, 0.25), (4, 0.75), (5, 0.5)]

def compute_rarity_scores_log(exemplars):
    """ Compute a score for each follower that is sum_i (1/n_i), where n_i is
    the degree of the ith exemplar they follow.
    >>> compute_rarity_scores({'e1':{1,2,3,4}, 'e2':{4,5}}).items()
    [(1, 0.25), (2, 0.25), (3, 0.25), (4, 0.75), (5, 0.5)]
    """
    scores = defaultdict(lambda: 0.)
    for followers in exemplars.values():
        score = 1. / math.log(len(followers))
        for f in followers:
            scores[f] += score
    return scores