Article "Kollegiengeld" in German Wikipedia has 18.5 points for quality (as of August 1, 2024). The article contains 3 references and 2 sections.
Since the creation of article "Kollegiengeld", its content was written by 12 registered users of German Wikipedia and edited by 12 registered Wikipedia users in all languages.
The article is cited 7 times in German Wikipedia and cited 7 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 August 1, 2024 (including revision history and pageviews for previous years).
| Best Rank | German: #531971 01.2018 |
Global: #4084696 01.2018 |
| Best Rank | German: #40364 04.2011 |
Global: #397855 04.2011 |
On 12 November 2024 in multilingual Wikipedia, Internet users most often read articles on the following topics: Donald Trump, Marco Rubio, Elon Musk, Song Jae-lim, 2024 United States presidential election, Megan Fox, Melania Trump, Gladiator II, ChatGPT, deaths in 2024.
In German Wikipedia the most popular articles on that day were: Vertrauensfrage, Liste der größten Auslegerbrücken, Peter Nidetzky, James Stewart, Michael Hübner (Radsportler), Departed – Unter Feinden, Katzendreckgestank-Affäre, Friedrich Merz, Marco Rubio, Donald Trump.
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 August, 2024. When calculating current popularity and AI of articles data from July 2024 was taken into account. For historical values of popularity and AI WikiRank used data from 2001 to 2023... More information
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(5.98+4.35+0+9.52+72.61)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
