Article “中國共產黨紀律處分條例” in Chinese Wikipedia has 20 points for quality (as of July 1, 2025). The article contains 4 references and 1 sections.
Since the creation of article “中國共產黨紀律處分條例”, its content was written by 6 registered users of Chinese Wikipedia and edited by 6 registered Wikipedia users in all languages.
The article is cited 174 times in Chinese Wikipedia and cited 174 times in all languages.
The highest Authors Interest rank from 2001:
The highest popularity rank from 2008:
There is 1 language version for this article in the WikiRank database (of the considered 55 Wikipedia language editions).
The quality and popularity assessment was based on Wikipédia dumps from July 1, 2025 (including revision history and pageviews for previous years).
| Best Rank | Chinese: #190831 05.2024 |
Global: #2836477 02.2025 |
| Best Rank | Chinese: #86325 07.2024 |
Global: #2493949 09.2022 |
On 18 November 2025 in multilingual Wikipedia, Internet users most often read articles on the following topics: 2026 FIFA World Cup, 2026 FIFA World Cup qualification (UEFA), 2026 FIFA World Cup qualification, Jeffrey Epstein, ChatGPT, Kessler Twins, Cloudflare, Sheikh Hasina, 2026 FIFA World Cup qualification (inter-confederation play-offs), 2026 FIFA World Cup qualification – UEFA second round.
In Chinese Wikipedia the most popular articles on that day were: 高市早苗, Cloudflare, 新聞女王2, 金刻羽, 親愛的X, 操控遊戲, 許紹雄, 武士生死鬥, Super Junior, 羅唯仁.
The WikiRank project is intended for automatic relative evaluation of the articles in the various language versions of Wikipedia. At the moment the service allows to compare over 44 million Wikipedia articles in 55 languages. Quality scores of articles are based on Wikipedia dumps from July, 2025. When calculating current popularity and AI of articles data from June 2025 was taken into account. For historical values of popularity and AI WikiRank used data from 2001 to 2025... More information
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(4.9+3.96+0+8.33+82.69)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
