Archive for the 'Brain' Category

Recent Roundup

Published on March 2, 2010 0 Comments

一些小体会，简单地记一下。

  • 最近的一次面试中，被问了一个 critical thinking 的问题。“假设你患了某种肾病，需要做肾脏移植才能康复。有用的信息是人类的肾脏有两种类型，A 和 B，但是在移植手术之前你即无法知道自己的类型也不知道捐献器官者的类型。假设在男性和女性中 A 型的比例分别是 p 和 q。现在有男女两个捐献者，你应该选择谁？”这其实是个非常简单的纯概率题（过程中我却以为是陷阱，给了一个自以为非常 smart 的答案）。If you do the math，it’s just straightforward。下图就是答案。
    match_prob
  • A few learnings from playing Texas Hold’em:
    1. 即使是零和博弈通货膨胀也能提高经济活动的活跃度；
    2. bailout 是玩家不多的时候经济稳定的基石；
    3. 自由竞争往往导致垄断；
    4. 为什么同花实际出现的概率要大于顺子呢？Poker Probability.

    A few learnings from playing Plants vs Zombies:

    1. 新时代的新问题要用新时代的新技术来解决；
    2. 大局观和局部战术都很重要，攻击要合理选择突破口，有重点。
  • 听说一个故事，想起 Adam Lambert 版本的 Tracks of My Tears。
Category: Brain Tags: , , .

[In Data] 一些中文 Twitter 用户的 Follower Similarity Index

Published on February 18, 2010 8 Comments

In an ongoing research project, we consider Twitter, the social network service, as a market, in which people produce and consume information by tweeting and following others. Let’s say user A and user B are two frequent tweeters. One interesting question would be “how similar” is the information contained in A’s and B’s tweets. One way to solve this question is of course do a semantic analysis of the two’s tweets. Another way, as we propose, is look at their respective followers. Presumably everyone has a preference on what kind of information she consumes, so her following someone should tell that, to some extent, she likes the one’s tweets. Therefore we can predict that if A’s and B’s tweets are similar, then they should have followers of similar preferences; inversely if A’s and B’s tweets are quite different, then the followers they attract should have quite different preferences.
We define Followers-Similarity-Index (FSI) of A and B as

For fun, I computed the FSIs for the following Chinese twitter users @flypig, @junyu, @turingbook, @mozhixu, @glif, @williamlong, @DashHuang, @Stefsunyanzi, @virushuo, @WangShuo, @xiaolai, @zuola, @wglxh, @wangpei, @gaojiamin, @ag108lau, @arthur369, @mranti, @songshinan, @hecaitou, @duanzi, @isaac, @shizhao, @luoyonghao, @jaqi, @jason5ng32, @maoz, @izlmichael, @roseluqiu, @livid, @onlyswan, @aiww, @fzhenghu, @zhangfacai. There are 34 people and hence C_{34}^{2}=561 combinations. I used the data collected at 0:00 Feb 17 CST. Below are the 561 computed FSIs sorted.

Category: Brain Tags: , , .