Article "Hey's Mineral Index" in English Wikipedia has 11.9 points for quality (as of August 1, 2024). The article contains 1 references and 3 sections.
Since the creation of article "Hey's Mineral Index", its content was written by 9 registered users of English Wikipedia and edited by 9 registered Wikipedia users in all languages.
The article is cited 17 times in English Wikipedia and cited 17 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 | English: #2907716 02.2019 |
Global: #5236474 02.2019 |
| Best Rank | English: #95783 01.2019 |
Global: #288366 01.2019 |
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 English Wikipedia the most popular articles on that day were: Microsoft, 2024 United States presidential election, Marco Rubio, Song Jae-rim, Michael Waltz, Kristi Noem, Donald Trump, 2020 United States presidential election, Kash Patel, Tom Homan.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(2.44+0.82+0+21.43+34.56)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
