techinsight.jp

Multilingual Wikipedia

In June 2020 the website techinsight.jp was on the 3,291st 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 8,680th place in June 2020. From Wikipedians' point of view, "techinsight.jp" is the 7,669th most reliable source in different language versions of Wikipedia (AR-score).

The website is placed before lexico.com and after google.fi in multilingual PR ranking of the most reliable sources in Wikipedia.

PR-score:
3,291st place
10,380,228
-2,674,543
AR-score:
7,669th place
571,234
-1,076
F-score:
8,680th place
1,434
+5

Japanese Wikipedia (ja)

PR-score:
231st place
9,870,438
-2,521,652
AR-score:
347th place
521,277
-498
F-score:
545th place
1,131
+4

English Wikipedia (en)

PR-score:
45,349th place
244,576
-110,755
AR-score:
61,013th place
20,289
+85
F-score:
40,433rd place
71
0

Chinese Wikipedia (zh)

PR-score:
4,129th place
227,480
-25,549
AR-score:
4,578th place
15,661
+59
F-score:
3,214th place
105
0

Indonesian Wikipedia (id)

PR-score:
7,753rd place
10,530
+1,071
AR-score:
4,936th place
3,773
+6
F-score:
4,053rd place
29
0

Spanish Wikipedia (es)

PR-score:
93,047th place
8,363
-147
AR-score:
66,488th place
2,197
+11
F-score:
35,329th place
11
0

Italian Wikipedia (it)

PR-score:
93,572nd place
2,508
-284
AR-score:
56,053rd place
2,072
0
F-score:
19,134th place
16
0
Show all Wikipedia languages...

Popularity and reliability assessment of sources in references of Wikipedia in different languages. Data extraction based on complex method using Wikimedia dumps in July 2020. To find the most popular and reliable sources we used information about over 200 million references of Wikipedia articles. More details in the research "Modeling Popularity and Reliability of Sources in Multilingual Wikipedia". Values for PR-score and AR-score were additinaly increased 100 times (to distinguish smaller values in the ranking).

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