Jean Ganière - French engraver and bookseller. Article “Jean Ganière” in French Wikipedia has 28.9 points for quality (as of July 1, 2025). The article contains 11 references and 6 sections.
Since the creation of article “Jean Ganière”, its content was written by 13 registered users of French Wikipedia and edited by 13 registered Wikipedia users in all languages.
The article is cited 4 times in French 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 | French: #618517 07.2019 |
Global: #5703426 07.2019 |
| Best Rank | French: #21861 10.2014 |
Global: #397332 10.2014 |
On 10 February 2026 in multilingual Wikipedia, Internet users most often read articles on the following topics: Jeffrey Epstein, Ghislaine Maxwell, Ilia Malinin, Bad Bunny, 2026 Winter Olympics, Epstein files, Jutta Leerdam, Jake Paul, Puerto Rico, Little Saint James.
In French Wikipedia the most popular articles on that day were: Jeffrey Epstein, Affaire Epstein, Amélie de Montchalin, Karine Le Marchand, Ghislaine Maxwell, Jack Lang, Adam Siao Him Fa, Bad Bunny, Michel-Ange, Howard Hughes.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(6.02+5.7+15.79+23.08+93.87)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
