Article "Vesprimense flórajárás" in Hungarian Wikipedia has 10 points for quality (as of August 1, 2024). The article contains 0 references and 8 sections.
Since the creation of article "Vesprimense flórajárás", its content was written by 12 registered users of Hungarian Wikipedia and edited by 12 registered Wikipedia users in all languages.
The article is cited 18 times in Hungarian Wikipedia and cited 18 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: #78487 05.2009 |
Global: #4440560 11.2008 |
| Best Rank | Hungarian: #11011 08.2013 |
Global: #783403 08.2008 |
On 2 March 2025 in multilingual Wikipedia, Internet users most often read articles on the following topics: Volodymyr Zelenskyy, Elon Musk, Gene Hackman, 97th Academy Awards, Donald Trump, JD Vance, Bob Dylan, The Brutalist, Michelle Trachtenberg, Pope Francis.
In Hungarian Wikipedia the most popular articles on that day were: 97. Oscar-gála, Hunyadi (televíziós sorozat), J. D. Vance, Busójárás, Gene Hackman, A brutalista, Ma este gyilkolunk, Volodimir Olekszandrovics Zelenszkij, Ruszin-Szendi Romulusz, Futni mentem.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(11.97+0+0+38.1+0)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
