Article “杉並区歴史教科書採択騒動” in Japanese Wikipedia has 15.4 points for quality (as of July 1, 2025). The article contains 10 references and 4 sections. The article also contains templates indicating quality issues, therefore its score was reduced by 0.81 points.
Since the creation of article “杉並区歴史教科書採択騒動”, its content was written by 17 registered users of Japanese Wikipedia and edited by 17 registered Wikipedia users in all languages.
The article is cited 4 times in Japanese Wikipedia and cited 4 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 | Japanese: #31271 07.2010 |
Global: #237744 07.2010 |
| Best Rank | Japanese: #25692 01.2025 |
Global: #827462 09.2012 |
On 26 September 2025 in multilingual Wikipedia, Internet users most often read articles on the following topics: Claudia Cardinale, One Battle After Another, ChatGPT, Alice in Borderland, Guinness, deaths in 2025, Benjamin Netanyahu, Assata Shakur, Charlie Kirk, Arthur Guinness.
In Japanese Wikipedia the most popular articles on that day were: 小川晶 (政治家), 小松暢, 沈黙の艦隊, やなせたかし, 牧島かれん, 今田美桜, 手塚治虫, 小泉八雲, 田中雄士, ベネット・ミラー.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(6.22+3.61+0+12.9+58.12)-0.81$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
