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oxfordhistory.org.uk

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Multilingual Wikipedia

In June 2020 the website oxfordhistory.org.uk was on the 51,607th 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 29,415th place in June 2020. From Wikipedians' point of view, "oxfordhistory.org.uk" is the 33,076th most reliable source in different language versions of Wikipedia (AR-score).

The website is placed before columbus.gov and after kintetsu-g-hd.co.jp in multilingual PR ranking of the most reliable sources in Wikipedia.

PR-score:
51,607th place
428,258
-43,168
AR-score:
33,076th place
101,988
+99
F-score:
29,415th place
332
+1

English Wikipedia (en)

PR-score:
30,439th place
391,776
-37,276
AR-score:
17,144th place
91,165
+59
F-score:
14,323rd place
253
0

Arabic Wikipedia (ar)

PR-score:
12,657th place
10,833
+3,700
AR-score:
39,020th place
933
+33
F-score:
111,637th place
1
0

Russian Wikipedia (ru)

PR-score:
107,101st place
6,703
-1,980
AR-score:
149,090th place
516
0
F-score:
83,101st place
4
0

Czech Wikipedia (cs)

PR-score:
18,883rd place
4,933
-933
AR-score:
20,190th place
1,133
0
F-score:
52,218th place
1
0

Spanish Wikipedia (es)

PR-score:
140,305th place
3,280
-1,917
AR-score:
140,487th place
632
0
F-score:
78,747th place
4
0

Chinese Wikipedia (zh)

PR-score:
76,224th place
3,249
+182
AR-score:
37,010th place
1,329
0
F-score:
21,138th place
11
0

German Wikipedia (de)

PR-score:
186,931st place
2,398
-2,299
AR-score:
67,326th place
3,461
-33
F-score:
27,378th place
17
0

Japanese Wikipedia (ja)

PR-score:
203,677th place
250
-200
AR-score:
162,593rd place
125
0
F-score:
50,968th place
6
0

Turkish Wikipedia (tr)

PR-score:
60,474th place
218
-45
AR-score:
38,747th place
364
0
F-score:
10,691st place
7
0
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About the project

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...

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