TUT.BY is an independent information and service website in the Russian language, one of the 5 most popular sites in Belarus and the most popular news web portal in the country. The headquarters is based in Minsk, Belarus. In 2019, the website was read by 62.58% of all Belarusian Internet users with monthly visits rate around 200 mln. More information...

Multilingual Wikipedia

In June 2020 the website tut.by was on the 1,432nd place in the ranking of the most reliable and popular sources in multilingual Wikipedia from readers' point of view (PR-score). If we consider only frequency of appearance of this source in references of Wikipedia articles (F-score), this website was on the 1,517th place in June 2020. From Wikipedians' point of view, "tut.by" is the 2,145th most reliable source in different language versions of Wikipedia (AR-score).

The website is placed before thecrimson.com and after lbl.gov in multilingual PR ranking of the most reliable sources in Wikipedia.

PR-score:
1,432nd place
25,457,693
-168,350
AR-score:
2,145th place
2,368,814
+32,522
F-score:
1,517th place
10,237
+372

Russian Wikipedia (ru)

PR-score:
101st place
21,038,911
+2,044,963
AR-score:
132nd place
1,554,462
+22,975
F-score:
163rd place
4,478
+209

English Wikipedia (en)

PR-score:
5,169th place
3,110,595
-1,768,678
AR-score:
10,471st place
159,493
+2,897
F-score:
6,411th place
657
+37

Belarusian Wikipedia (be)

PR-score:
4th place
414,071
-86,172
AR-score:
9th place
241,175
+2,518
F-score:
11th place
1,921
+37

Ukrainian Wikipedia (uk)

PR-score:
538th place
239,393
-64,651
AR-score:
491st place
76,142
+1,058
F-score:
541st place
422
+39

Polish Wikipedia (pl)

PR-score:
4,264th place
118,464
-48,911
AR-score:
1,683rd place
57,555
+215
F-score:
622nd place
789
+3

Belarusian (Taraškievica) Wikipedia (be-x-old)

PR-score:
12th place
100,364
-30,158
AR-score:
12th place
138,666
+2,516
F-score:
11th place
855
+16
Show all Wikipedia languages...

BestRef shows popularity and reliability scores for sources in references of Wikipedia articles in different languages. Data extraction based on complex method using Wikimedia dumps. To find the most popular and reliable sources we used information about over 200 million references of Wikipedia articles. More details...