mha.nic.in

Multilingual Wikipedia

In June 2020 the website mha.nic.in was on the 2,959th 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 2,744th place in June 2020. From Wikipedians' point of view, "mha.nic.in" is the 2,468th most reliable source in different language versions of Wikipedia (AR-score).

The website is placed before akitashoten.co.jp and after eastday.com in multilingual PR ranking of the most reliable sources in Wikipedia.

PR-score:
2,959th place
11,750,927
-1,673,238
AR-score:
2,468th place
2,035,225
+5,425
F-score:
2,744th place
5,272
+31

English Wikipedia (en)

PR-score:
1,749th place
10,585,126
-1,915,207
AR-score:
1,249th place
1,703,474
-1,180
F-score:
1,894th place
2,517
+1

Chinese Wikipedia (zh)

PR-score:
2,338th place
431,998
+250,515
AR-score:
10,441st place
6,119
-890
F-score:
6,428th place
45
0

Hindi Wikipedia (hi)

PR-score:
98th place
117,191
-1,672
AR-score:
95th place
56,106
+2,942
F-score:
177th place
171
+1

Japanese Wikipedia (ja)

PR-score:
15,125th place
87,190
+56,027
AR-score:
30,573rd place
3,005
-128
F-score:
16,113th place
24
0

Russian Wikipedia (ru)

PR-score:
29,217th place
52,459
-165
AR-score:
20,998th place
7,671
+23
F-score:
23,029th place
22
0

Tamil Wikipedia (ta)

PR-score:
188th place
35,253
-10,494
AR-score:
137th place
31,906
+11
F-score:
115th place
342
0

Malayalam Wikipedia (ml)

PR-score:
121st place
31,785
+5,456
AR-score:
100th place
35,338
+902
F-score:
126th place
224
0

Bengali Wikipedia (bn)

PR-score:
287th place
30,505
-5,459
AR-score:
194th place
25,920
+870
F-score:
192nd place
261
0

Punjabi Wikipedia (pa)

PR-score:
129th place
9,339
-288
AR-score:
68th place
10,722
+42
F-score:
51st place
208
+2
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...