Article “Stephen Marr” in German Wikipedia has 33.6 points for quality (as of July 1, 2025). The article contains 24 references and 4 sections.
Since the creation of article “Stephen Marr”, its content was written by 9 registered users of German Wikipedia and edited by 9 registered Wikipedia users in all languages.
The article is cited 2 times in German 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 | German: #414575 12.2017 |
Global: #3285417 12.2017 |
| Best Rank | German: #2058 12.2017 |
Global: #85299 12.2017 |
On 10 March 2026 in multilingual Wikipedia, Internet users most often read articles on the following topics: Iran, Mojtaba Khamenei, Enhypen, Ali Khamenei, Strait of Hormuz, Jeffrey Epstein, 2026 Iran war, 2026 World Baseball Classic, Donald Trump, World Baseball Classic.
In German Wikipedia the most popular articles on that day were: Cem Özdemir, Wanda Perdelwitz, Luise von Mecklenburg-Strelitz, Liste der größten Auslegerbrücken, Landtagswahl in Baden-Württemberg 2026, Dot Rotten, Guido Westerwelle, Manuel Hagel, Boris Palmer, Irankrieg 2026.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(14.77+34.29+0+19.05+100)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
