Category Archives: papers

十八般武艺，谁主天下？(Ranking of Weapons in Chinese Kung-Fu Novels)

Today a friend asked me what I did in the Ranking of Weapons in Chinese Kung-Fu Novels article. Here is the backup copy of my reply.

Chinese link: http://cos.name/2013/02/jinyong-fiction-mining/

-------------the analysis----------------

  • Find raw texts for 14 novels by a famous Chinese Kungfu novel writer. Each novel is at least 100K Chinese words long.
  • Do some natural language processing technics… mainly filter the weapon and character name keywords from the long texts.
  • Define a relationship (formally links in a network) between two keywords if they appear in the same paragraphs.
  • Do the social network analysis. So you see the graphs here : http://cos.name/2013/02/jinyong-fiction-mining/
  • Rank these weapons by their pagerank score in the network. e.g.

剑Sword  0.018411053
刀Knife   0.017516021
掌Palm  0.017137869
抓  0.011880115
拳Fist  0.011605281

  • some other analysis, e.g. clustered by novels, relationships between characters, etc.

[Publication] Perhaps...the first publication under BGSE in Chinese

At the end of last month, I was notified that one of my papers co-authored with my previous advisor, Yue Qiao, was accepted. Today I downloaded an electronic version of it and finally confirmed.

That paper is published with the title The Mechanism Evolution and Information Transmission in Online Markets (我国网上交易的机制演化与信息传导) , at the Journal of Zhongnan University of Economics and Law, 2012, 192 (03). At the moment when we submitted the paper, I was studying at the Barcelona Graduate School of Economics, so interestingly the institution behind my name is BGSE in the published version.

I should say it is an old paper - and I have waited for three years to get it published. It is not a short time period - as I have graduated and have already changed a job. On the other hand, the paper is about mechanisms in online C2C market (Taobao.com as the context), and now I am working at eBay and am committed to C2C behavior analysis. Sounds like a regression, right?

Perhaps it is the version reason why I chose eBay immediately right after I got their offer. Theories need to be examined in the real market environment, and eBay is exactly the right place to do this! I have no reason not to be excited about working here. As the theoretical research is accepted, I should spend more time on the empirical part now. Hopefully, these years of knowledge gaining and work experience will enhance my analytical thinking ability and get a fruitful result afterwards.

I'm going on the way, and there is no word called "give up" in my dictionary.

The print version of this paper in Chinese can be download here: Mechanism_evolution_C2C.pdf

The social network of economists

Recently I fell in love with social network... Therefore, it is unavoidable to add some social network analysis results into my graduation thesis. Here are some interesting graphs used in my paper, which I would like to share with you online. They are all about "the social network of economists", i.e. the academic circle of economics.

all_10_nolabel

Full view of the economists' world, without labels.

The bigger size of nodes denotes the higher level of connections with others (degree/pagerank). (2000-present). An expandable vector diagram can be download here:  all_10_nolabel.pdf
top_10_grey

Full view of economists' world, with grey edges (2000-present)

all_10_main_all_label

The structure (reduced) of economists' social network, with labels of names (2000-present).

An expandable vector diagram can be download here: all_10_main_all_label.pdf

[Update July]

Here is a specific analysis of the "Law and Economics" sub-field. Data source is from all published papers (6,319 in total) under JEL classification K: Law and Economics. Available at RePEc.org.

law and economics

Here is the PDF version: academic circle of law and economics.pdf

You can find more graphs by continuing reading.
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What Do We Pay For Asymmetric Information? The Mechanism Evolution of Reputation, Punishment and Barriers to Entry in Online Markets

Well, in fact it is not a piece of news. It is the title of a paper I wrote last winter. After finishing it, I went on doing something else and forgot it. Now it is already a new spring, I do not want to submit it to any journals since I have nothing fresh to add into it. Without anything new, I don't have the incentive to edit it. Therefore, I share it with you here.

Title

What Do We Pay For Asymmetric Information? The Mechanism Evolution of Reputation, Punishment and Barriers to Entry in Online Markets

Abstract

The appearance of the Internet reduces transaction costs greatly, and brings the boom of online markets. While we are trying to regard it as the most realistic approximation of perfect competition market, the asymmetric information and a series of problems caused by it stop us from dreaming. As the old saying goes, there is no free lunch. This summer witnessed the collapse of the reputation system in Taobao, the biggest online transaction website in China. In fact, during the evolution of mechanisms in online markets, reputation, punishment and barriers to entry have been established in turn. What do we pay for maintaining these mechanisms? In which circumstance will they be effective?

In this paper I try to build a series of models within the principal-agent framework and repeated games to explain why and what we should pay for asymmetric information while enjoying shopping online. Specifically, these mechanisms are considered step by step and their boundary validation conditions are discussed. Finally, as the conclusion indicates, in a larger range that a mechanism is effective, the more opportunity cost should be paid as a rent for information.

Download (English Version)

Copyright Announcement: Please do not change any content without my permission. Please do not use it for commercial purpose. Please do not publish it anywhere else.

If you would like to mention or quote it in your article, please link it to this page or copy this link: What Do We Pay For Asymmetric Information? The Mechanism Evolution of Reputation, Punishment and Barriers to Entry in Online Markets

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