Article "किहूँ वंश" in Hindi Wikipedia has 0.4 points for quality (as of August 1, 2024). The article also contains quality flaw template, which reduce quality score.
Since the creation of article "किहूँ वंश", its content was written by 4 registered users of Hindi Wikipedia and edited by 4 registered Wikipedia users 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 | Hindi: #29350 11.2016 |
Global: #6746851 11.2016 |
On 6 November 2024 in multilingual Wikipedia, Internet users most often read articles on the following topics: Donald Trump, 2024 United States presidential election, Kamala Harris, 2020 United States presidential election, United States Electoral College, President of the United States, 2016 United States presidential election, Melania Trump, list of presidents of the United States, Joe Biden.
In Hindi Wikipedia the most popular articles on that day were: शारदा सिन्हा, छठ पूजा, संयुक्त राज्य के राष्ट्रपतियों की सूची, कमला हैरिस, डॉनल्ड ट्रम्प, क्लियोपाट्रा ७, संयुक्त राज्य राष्ट्रपति चुनाव, 2024, संयुक्त राज्य अमेरिका का राष्ट्रपति, जो बाइडन, भारत के राज्य तथा केन्द्र-शासित प्रदेश.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(2.04+0+0+0+0)-0.04$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
