2019 EE6 - TNO. Article “2019 EE6” in French Wikipedia has 18.2 points for quality (as of July 1, 2025). The article contains 3 references and 3 sections.
Since the creation of article “2019 EE6”, its content was written by 3 registered users of French Wikipedia and edited by 3 registered Wikipedia users in all languages.
The article is cited 2 times in French Wikipedia and cited 2 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: #878743 04.2023 |
Global: #7092612 04.2023 |
| Best Rank | French: #22831 04.2023 |
Global: #465858 04.2023 |
On 15 February 2026 in multilingual Wikipedia, Internet users most often read articles on the following topics: Jeffrey Epstein, Wuthering Heights, 2026 Winter Olympics, Epstein files, Ilia Malinin, Wuthering Heights, Ghislaine Maxwell, Lucas Pinheiro Braathen, 2026 Winter Olympics medal table, Valentine's Day.
In French Wikipedia the most popular articles on that day were: Jeffrey Epstein, Platoon, Collectif Némésis, Sophie Adenot, Martin Fourcade, Gisèle Pelicot, Affaire Epstein, Rima Hassan, Pavel Kovalev, André Dussollier.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(2.19+1.55+5.26+11.54+70.46)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
