Leopold Weisz - victim of Titanic disaster. Article "Leopold Weisz" in Hungarian Wikipedia has 14.2 points for quality (as of August 1, 2024). The article contains 3 references and 5 sections.
Since the creation of article "Leopold Weisz", its content was written by 7 registered users of Hungarian Wikipedia and edited by 7 registered Wikipedia users in all languages.
The article is cited 1 times in Hungarian Wikipedia and cited 1 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: #21840 06.2023 |
Global: #2215601 06.2023 |
| Best Rank | Hungarian: #1837 10.2018 |
Global: #440231 10.2018 |
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(9.63+3.26+0+23.81+34.1)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
