Article "Єребакан Дмитро Дмитрович" in Ukrainian Wikipedia has 8.5 points for quality (as of August 1, 2024). The article contains 1 references and 4 sections.
Since the creation of article "Єребакан Дмитро Дмитрович", its content was written by 2 registered users of Ukrainian Wikipedia and edited by 2 registered Wikipedia users in all languages.
The article is cited 28 times in Ukrainian Wikipedia and cited 28 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 | Ukrainian: #201471 10.2022 |
Global: #7549343 10.2022 |
| Best Rank | Ukrainian: #9508 08.2021 |
Global: #1036551 08.2021 |
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 Ukrainian Wikipedia the most popular articles on that day were: Джей Ді Венс, Дональд Трамп, Будапештський меморандум, YouTube, Зеленський Володимир Олександрович, Порцелянова війна, Уша Венс, Ілон Маск, Масниця, Вінстон Черчилль.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(7.05+1.14+0+17.39+16.69)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
