Article "Perényi Gábor (főkamarás)" in Hungarian Wikipedia has 27.5 points for quality (as of August 1, 2024). The article contains 11 references and 4 sections.
Since the creation of article "Perényi Gábor (főkamarás)", its content was written by 5 registered users of Hungarian Wikipedia and edited by 5 registered Wikipedia users in all languages.
The article is cited 2 times in Hungarian 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 August 1, 2024 (including revision history and pageviews for previous years).
| Best Rank | Hungarian: #96110 10.2015 |
Global: #6680578 10.2015 |
| Best Rank | Hungarian: #2025 10.2015 |
Global: #473302 10.2015 |
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 Hungarian Wikipedia the most popular articles on that day were: S.E.R.E.G., Márton-napi népszokások, Nemere István, Donald Trump, Simon Attila (labdarúgó, 1983), November 12., Csórics Balázs, Megan Fox, Magyarország, 2024-es amerikai elnökválasztás.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(6.53+11.96+0+19.05+100)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
