Grand-Heid - human settlement in Lierneux, Belgium. Article “Grand-Heid” in French Wikipedia has 8.7 points for quality (as of July 1, 2025). The article contains 0 references and 4 sections.
Since the creation of article “Grand-Heid”, its content was written by 1 registered users of French Wikipedia and edited by 1 registered Wikipedia users in all languages.
The article is cited 23 times in French Wikipedia and cited 23 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 | French: #522452 03.2023 |
Global: #4480584 03.2023 |
| Best Rank | French: #221774 07.2018 |
Global: #1619235 06.2015 |
On 10 February 2026 in multilingual Wikipedia, Internet users most often read articles on the following topics: Jeffrey Epstein, Ghislaine Maxwell, Ilia Malinin, Bad Bunny, 2026 Winter Olympics, Epstein files, Jutta Leerdam, Jake Paul, Puerto Rico, Little Saint James.
In French Wikipedia the most popular articles on that day were: Jeffrey Epstein, Affaire Epstein, Amélie de Montchalin, Karine Le Marchand, Ghislaine Maxwell, Jack Lang, Adam Siao Him Fa, Bad Bunny, Michel-Ange, Howard Hughes.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(1.84+0+26.32+15.38+0)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
