Miklós Kőszeghy - Hungarian historian. Article "Kőszeghy Miklós" in Hungarian Wikipedia has 19 points for quality (as of August 1, 2024). The article contains 4 references and 4 sections. The article also contains quality flaw template, which reduce quality score.
Since the creation of article "Kőszeghy Miklós", its content was written by 20 registered users of Hungarian Wikipedia and edited by 20 registered Wikipedia users 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: #51447 04.2008 |
Global: #3493588 01.2008 |
| Best Rank | Hungarian: #1585 04.2006 |
Global: #329569 04.2006 |
On 19 November 2024 in multilingual Wikipedia, Internet users most often read articles on the following topics: Mike Tyson, Elon Musk, MGM-140 ATACMS, Gladiator II, International Men's Day, 2024–25 UEFA Nations League, Donald Trump, Jake Paul, Jon Jones, deaths in 2024.
In Hungarian Wikipedia the most popular articles on that day were: Kozák Danuta, A sikoly, Nemzetközi férfinap, Dili, Bodnár (foglalkozás), Fahrenheit, Bostoni teadélután, November 19., Vasvári Vivien, Drávucz Rita.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(6.25+4.35+0+19.05+70.12)-1$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
