تقييم الاحتياجات

AR

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تقييم الاحتياجات

Needs assessment - systematic identification of a population's needs or assessment of individuals to determine the level of services needed. Article "تقييم الاحتياجات" in Arabic Wikipedia has 24.8 points for quality (as of January 1, 2021). The article contains, among others metrics, 19 references and 5 sections.

This article has the best quality in English Wikipedia. Also, this article is the most popular in that language version.

Achievements in December 2020:

Since the creation of article "تقييم الاحتياجات", its content was written by 11 authors in Arabic Wikipedia and edited by 143 authors in all languages.

The article is cited 5 times in Arabic Wikipedia and cited 35 times in all languages.

The highest Authors’ Interest rank from 2002:

  • Local (Arabic): #11125 in October 2010
  • Global: #143497 in September 2012

The highest popularity rank from 2008:

  • Local (Arabic): #25958 in February 2019
  • Global: #73347 in March 2015

There are 5 language versions for this article in WikiRank database (of the considered 55 Wikipedia language editions).

The quality and popularity assessment was based on Wikipedia dumps from January 1, 2021 (including revision history and pageviews for previous years).

The table below shows the language versions of the article with the highest quality.

Languages with the highest quality

#LanguageQuality gradeQuality score
1English
Needs assessment
60.2277
2Arabic
تقييم الاحتياجات
24.8125
3Ukrainian
Оцінка потреб
23.3225
4Korean
요구 분석
19.733
5Persian
نیازسنجی
15.4111
More...

The following table shows the most popular language versions of the article.

Most popular in December 2020

The most popular language versions of the article "تقييم الاحتياجات" in December 2020
#LanguagePop. awardRelative popularity
1English
Needs assessment
100
2Arabic
تقييم الاحتياجات
3.538
3Persian
نیازسنجی
3.2432
4Ukrainian
Оцінка потреб
2.474
5Korean
요구 분석
0.3204
More...

The following table shows the language versions of the article with the highest Authors’ Interest.

The highest AI in December 2020

Language versions of the article "تقييم الاحتياجات" with the highest AI in December 2020
#LanguageAI awardRelative AI
1Arabic
تقييم الاحتياجات
NAN
2English
Needs assessment
NAN
3Persian
نیازسنجی
NAN
4Korean
요구 분석
NAN
5Ukrainian
Оцінка потреб
NAN
More...

The following table shows the language versions of the article with the highest number of citations.

The highest CI

Language versions of the article "تقييم الاحتياجات" with the highest Citation Index (CI)
#LanguageCI awardRelative CI
1English
Needs assessment
100
2Arabic
تقييم الاحتياجات
19.2308
3Persian
نیازسنجی
7.6923
4Ukrainian
Оцінка потреб
7.6923
5Korean
요구 분석
0
More...

Scores

Quality as of January 1, 2021:
Popularity in December 2020:
Arabic:
Global:
Authors in December 2020:
Arabic:
Global:
Authors in all years:
Arabic:
Global:
Citations:
Arabic:
Global:

Quality measures

Interwiki

Popularity rank history

Best Rank Arabic:
#25958
02.2019
Global:
#73347
03.2015

AI rank history

Best Rank Arabic:
#11125
10.2010
Global:
#143497
09.2012

Languages comparsion

Cumulative results

News from 26 February 2021

On 26 February 2021 in multilingual Wikipedia, Internet users most often read articles on the following topics: WandaVision, Scarlet Witch, Daft Punk, Elizabeth II, YouTube, Deaths in 2021, Cleopatra, Lantern Festival, Agatha Harkness, February 26.

In Arabic Wikipedia the most popular articles on that day were: مشاري البلام, حسن البلام, يوسف شعبان, بودي جارد (مسرحية), سورة الكهف, علي بن أبي طالب, حسينيون, باي تونس, عثمان الأول, بيتكوين.

About WikiRank

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 39 million Wikipedia articles in 55 languages. Quality scores of articles are based on Wikipedia dumps from January, 2021. When calculating current popularity and AI of articles data from December 2020 was taken into account. For historical values of polularity and AI WikiRank used data from 2002 to 2020... More information