To find out that which author do people find most inspiring, we used the link structure of Wikipedia. First we extracted the link structure of Wikipedia and create the adjacency matrix, then we apply an eigenanalysis method, which is also called PageRank, to answer the first question. We showed the results of German, English, and Japanese authors. We also compared the same category (authors), but between the different data source, i.e., different language Wikipedia. We can see the interesting similarity and also difference. Personally, one of the authors was surprised me that Winston Churchill and Issac Newton have a high ranking score. He didn't know Winston Churchill is the Nobel Prize winner of the literature.
Recently, I use a mathematical approach or an information scientific approach to understand literature and languages. This approach has a huge limitation, but on the other hand, it gives me some measureable values. Brené Brown said in her TED talk , ``Maybe stories are just data with a soul.'' Maybe so. And I think the soul can cast a vague shadow on data. I agree that we can not reconstruct the soul now. However, reading a book is just an act of reading symbol sequence -- reading data sequence --, I still know my soul can be moved by the act. I want to see a footprint of the soul in the data. This article is one of this kind of trial. I don't know how to call this approach, therefore, tentatively, I call this approach ``Computational literature,'' until I found a better name.
We summarize the future work:
- Are there any bias based on Wikipedia writers? (Ditger v A.)
- How can we avoid the category problem. How can we automatize the data collection.
- Apply other graph analysis methods. We only apply the eigenanalysis (PageRank) in this article.
- We saw the adjacency matrix has some property (e.g., not full rank). We can deeply look into the graph structure using some graph theory tool.
- It is interesting to apply this method to other language authors.
- This method is not limited to authors. We can apply this method to other area, for example, actors, musicians, politicians, mathematicians, and so on.
This was a relatively large project as a Sunday research, it took almost half a year. But, this was fun.
I thank to all the friends who gave me a lot of useful comments at the lunch time. Thanks to Andy K. to check some part of my English in part 1. I thank to Rebecca M., who first asked me the question. This project doesn't exist if she didn't ask me the question.