Article “Vävram” in Swedish Wikipedia has 1.8 points for quality (as of July 1, 2025). The article also contains templates indicating quality issues, therefore its score was reduced by 0.1 points.
Since the creation of article “Vävram”, its content was written by 5 registered users of Swedish Wikipedia and edited by 5 registered Wikipedia users in all languages.
The article is cited 55 times in Swedish Wikipedia and cited 55 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 | Swedish: #123603 04.2019 |
Global: #3325035 01.2008 |
| Best Rank | Swedish: #9373 09.2004 |
Global: #285654 09.2004 |
On 15 February 2026 in multilingual Wikipedia, Internet users most often read articles on the following topics: Jeffrey Epstein, Wuthering Heights, 2026 Winter Olympics, Epstein files, Ilia Malinin, Wuthering Heights, Ghislaine Maxwell, Lucas Pinheiro Braathen, 2026 Winter Olympics medal table, Valentine's Day.
In Swedish Wikipedia the most popular articles on that day were: Martin Ponsiluoma, Sara Hector, Dolph Lundgren, Hanna Öberg, Jyrki Ponsiluoma, Anja Pärson, Calle Halfvarsson, Korslagda, Margit Sahlin, Jan Boklöv.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(1.24+0+8.33+0+0)-0.1$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
