week13: read Wikipedia:Categorization --LAOXINYI

  1）Summary

Have you ever noticed that every time you browse an entry on Wikipedia, there are a few small blue words listed at the bottom of the page - they are usually links starting with "Category:", such as "Category: 20th Century French Novels" or "Category: Biologists"? These categories are not decorations, but the "capillaries" that make the Wikipedia system run.

The categorization system makes Wikipedia look like an orderly knowledge network, rather than a pile of scattered entries. There is a rigorous logic behind this and many design details worth exploring. From "categorizing articles" to "creating new category pages", to how to prevent the classification tree from becoming a mess, the editors have quietly done a lot of "invisible engineering" behind the scenes.


2）Interesting Point

I think the most interesting thing is that Wikipedia's classification system is like a well-designed knowledge map. You may not notice it, but it is through these classifications that readers can expand from a detail to the entire field. For example, if you are reading an entry about "Paris", you can not only see that it is classified under "French cities", but also find other content related to "French cities" without having to conduct additional searches.

In addition, the settings of sorting keys and classification levels also make me feel quite clever: for example, when dealing with names, the system recommends using the "surname, first name" sorting method; when dealing with place names with prefixes, there are also special rules to ensure the accuracy of the sorting. This meticulous design not only facilitates readers, but also makes the entire Wikipedia structure look orderly, as if each entry has found its "home".


3）Discussion

So, what impact does this classification system have on Wikipedia?

Comments

  1. ljhwaApril 14, 2025 at 9:17 AM

    This kind of classification system encourages people to stay longer on Wikipedia. In particular, naturally exposing related content increases the likelihood that a user will read those articles. This is because it can be assumed that if someone came to gain information from the first article, they would not want to miss the opportunity to encounter other related information.

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