List of former Soviet Republics by GDP - Wikimedia list article. Article "فہرست سابقہ سوویت ریاستیں بلحاظ خام ملکی پیداوار (مساوی قوت خرید)" in Urdu Wikipedia has 0.5 points for quality (as of July 1, 2025).
Since the creation of article "فہرست سابقہ سوویت ریاستیں بلحاظ خام ملکی پیداوار (مساوی قوت خرید)", its content was written by 2 registered users of Urdu Wikipedia and edited by 2 registered Wikipedia users in all languages.
The article is cited 17 times in Urdu 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 July 1, 2025 (including revision history and pageviews for previous years).
| Best Rank | Urdu: #12787 09.2013 |
Global: #8281050 09.2013 |
On 12 August 2025 in multilingual Wikipedia, Internet users most often read articles on the following topics: Cristiano Ronaldo, Wednesday, Georgina Rodríguez, ChatGPT, Weapons, Jenna Ortega, deaths in 2025, Taylor Swift, Miguel Uribe Turbay, 2025–26 UEFA Champions League.
In Urdu Wikipedia the most popular articles on that day were: یوم آزادی بھارت, یوم آزادی پاکستان, جنگ آزادی ہند 1857ء, انا لله و انا الیه راجعون, پاکستان, محمد بن عبد اللہ, بابڑہ قتل عام, علی ہجویری, محمد علی جناح, عمر بن خطاب.
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 July, 2025. When calculating current popularity and AI of articles data from June 2025 was taken into account. For historical values of popularity and AI WikiRank used data from 2001 to 2025... More information
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(2.51+0+0+0+0)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
