Article "ガルエージェンシー" in Japanese Wikipedia has 9.7 points for quality (as of November 1, 2023). The article contains 3 references and 5 sections. The article also contains quality flaw template, which reduce quality score.
In October 2023 the article "ガルエージェンシー" was edited by 1 authors in Japanese Wikipedia and written by 1 authors in all languages.
Since the creation of article "ガルエージェンシー", its content was written by 81 registered users of Japanese Wikipedia and edited by 81 registered Wikipedia users in all languages.
The article is cited 17 times in Japanese Wikipedia and cited 17 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 November 1, 2023 (including revision history and pageviews for previous years).
| Best Rank | Japanese: #21818 11.2011 |
Global: #214100 11.2011 |
On 30 May 2024 in multilingual Wikipedia, Internet users most often read articles on the following topics: Feast of Corpus Christi, YouTube, Vincent Kompany, Hansi Flick, UEFA Europa Conference League, deaths in 2024, ChatGPT, Olympiacos F.C., Furiosa: A Mad Max Saga, UEFA Euro 2024.
In Japanese Wikipedia the most popular articles on that day were: 岡部たかし, 内田有紀, 川田亜子, 那須雪崩事故, 山﨑福也, 蓮舫, 永野芽郁, 水谷瞬, 三淵嘉子, 松任谷由実.
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 November, 2023. When calculating current popularity and AI of articles data from October 2023 was taken into account. For historical values of popularity and AI WikiRank used data from 2001 to 2023... More information
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(3.71+1.11+0+16.13+29.99)-0.51$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
