Article “ОШ „Франце Прешерн” Раковица” in Serbian Wikipedia has 24.3 points for quality (as of July 1, 2025). The article contains 10 references and 3 sections.
Since the creation of article “ОШ „Франце Прешерн” Раковица”, its content was written by 4 registered users of Serbian Wikipedia and edited by 4 registered Wikipedia users in all languages.
The article is cited 37 times in Serbian Wikipedia and cited 37 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 | Serbian: #54057 11.2021 |
Global: #5387704 11.2021 |
| Best Rank | Serbian: #5687 12.2023 |
Global: #1084048 12.2023 |
On 7 October 2025 in multilingual Wikipedia, Internet users most often read articles on the following topics: Ed Gein, Ilse Koch, Lizzie Borden, Anthony Perkins, Monster: The Ed Gein Story, Greta Thunberg, Richard Speck, Psycho, ChatGPT, Charlie Hunnam.
In Serbian Wikipedia the most popular articles on that day were: Халид Бешлић, Бака Прасе, Едуард Бакарец, Стефан Немањић, Стефан Немања, Немањићи — рађање краљевине, Црна свадба (2. сезона), Вукан Немањић, Кнежина (Соколац), Зорана Мићановић.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(3.65+5.65+0+12+100)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
