松山車站 (台灣)

Quality:

Songshan station - railway station located in Taipei, Taiwan. This building is the 349^th most popular in Chinese Wikipedia. Article “松山車站 (台灣)” in Chinese Wikipedia has 85.9 points for quality (as of July 1, 2025). The article contains 73 references and 17 sections.

In this language version of Wikipedia the article has the best quality. Also, this article is the most popular in that (Chinese) language version.

Achievements in all the time:

Chinese Wikipedia:

zh

The 1755^th most editable in Chinese Wikipedia.

The 349^th most popular in buildings in Chinese Wikipedia.

Since the creation of article “松山車站 (台灣)”, its content was written by 202 registered users of Chinese Wikipedia (1755^th place) and edited by 327 registered Wikipedia users in all languages.

Songshan station is on the 349^th place in local ranking of buildings on Chinese Wikipedia in all the time.

The article is cited 294 times in Chinese Wikipedia and cited 732 times in all languages.

The highest Authors Interest rank from 2001:

• Local (Chinese): #52 in November 2014
• Global: #4430 in November 2014

The highest popularity rank from 2008:

• Local (Chinese): #4397 in November 2014
• Global: #181821 in July 2016

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

The quality and popularity assessment was based on Wikipédia dumps from July 1, 2025 (including revision history and pageviews for previous years).

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

#	Language	Quality grade	Quality score
1	Chinese (zh) 松山車站 (台灣)		85.914
2	English (en) Songshan station		55.8768
3	Japanese (ja) 松山駅 (台北市)		50.2282
4	Vietnamese (vi) Ga Tùng Sơn		31.8417
5	Simple English (simple) Songshan station		5.2806

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

#	Language	Popularity award	Relative popularity
1	Chinese (zh) 松山車站 (台灣)		329 047
2	Japanese (ja) 松山駅 (台北市)		91 117
3	English (en) Songshan station		77 248
4	Vietnamese (vi) Ga Tùng Sơn		644
5	Simple English (simple) Songshan station		250

The following table shows the language versions of the article with the highest popularity in the last month.

#	Language	Popularity award	Relative popularity
1	Chinese (zh) 松山車站 (台灣)		1 705
2	English (en) Songshan station		341
3	Japanese (ja) 松山駅 (台北市)		314
4	Vietnamese (vi) Ga Tùng Sơn		25
5	Simple English (simple) Songshan station		10

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

#	Language	AI award	Relative AI
1	Chinese (zh) 松山車站 (台灣)		202
2	English (en) Songshan station		65
3	Japanese (ja) 松山駅 (台北市)		56
4	Simple English (simple) Songshan station		2
5	Vietnamese (vi) Ga Tùng Sơn		2

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

#	Language	AI award	Relative AI
1	English (en) Songshan station		0
2	Japanese (ja) 松山駅 (台北市)		0
3	Simple English (simple) Songshan station		0
4	Vietnamese (vi) Ga Tùng Sơn		0
5	Chinese (zh) 松山車站 (台灣)		0

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

On 26 September 2025 in multilingual Wikipedia, Internet users most often read articles on the following topics: Claudia Cardinale, One Battle After Another, ChatGPT, Alice in Borderland, Guinness, deaths in 2025, Benjamin Netanyahu, Assata Shakur, Charlie Kirk, Arthur Guinness.

In Chinese Wikipedia the most popular articles on that day were: 于朦胧, 今際之國的闖關者 (電視劇), 堰塞湖, BOYS II PLANET, 暴君的廚師, 鏈鋸人, 宋伊人, 颱風樺加沙, 馬太鞍溪堰塞湖溢流, 傅崐萁.

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 44 million Wikipedia articles in 55 languages. Quality scores of articles are based on Wikipedia dumps from July, 2025. When calculating current popularity and AI of articles data from June 2025 was taken into account. For historical values of popularity and AI WikiRank used data from 2001 to 2025... More information