Around the World with MVPs: Microsoft Three Musketeers!
Published May 29 2019 03:41 PM 2,317 Views
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This article was written by Rie Moriguchi, Microsoft Community Program Manager - Japan. 


Microsoft provides localized technical documentation on various Microsoft services and products, and localized open source products for developers around the world. To make these localized materials better suited and available for local developers we decided to put on a unique community localization project for the 88 Microsoft MVPs and 32 community leaders from China, Japan, and Korea. We called it Microsoft Three Musketeers! Here’s what we go up to.


It was a fun, competition-style event where attendees competed in various activities, such as adding suggestions through Pull Request about critical localization error and the lack of explanation on existing localized technical documentation (, and voting or adding new strings suggestions on Microsoft Localization Community Platform (MLCP).


Participants also created attractive blog and social media content, demonstrating how best to join the community localization on and MLCP, and Microsoft Learn. 


Their passion to improve the quality of the localized contents and products brought about a significant result. Surprisingly, the number of approved suggestions on reached 7,000, and 4,300 strings were newly approved on MLCP during this project in a single month! What’s more, community localization introduction content reached 21,000, resulting in more members understanding and getting to know the open community activities on Microsoft Docs, MLCP and Microsoft Learn thanks to the participants’ efforts.


After the competition we held a Celebration Day Event in each country with the participants. Microsoft HQ DevRel Localization Team members joined this event and celebrated for our great “Musketeers.”


Here are the top 3 winning teams from the three countries and some of our favorite content that was published by attendees:



Top 3 Teams:

1. Minzhang He

2. Team4(刘俊哲shelley Liu, 张煜, 刘瑞恒, 依婷婷)

3. Xiaodi Yan

Picked Up Content:



Top 3 Teams:

1. Translation Uncles (번역AJ)

2. Underdog(언더독)

3. Untitle(언타이틀), Azaer(아재)

Picked Up Content:



Top 3 Teams:

1. No Name (ノーネーム)

2. Various Expertise Heroes

3. Nombiri Sorosoro (のんびりそろそろ)

Picked Up Content:

You can watch the interview videos in each country here.  


Nowadays, a lot of localized content is usually generated by machine translation to keep up with the latest technology day by day. Your feedback is therefore key to improving the quality of content as a practical development experience. It is highly important to fill in the gaps between machine-translated localization and the best references for local developers.


Interested in starting your own community localization project? Head to the Cloud + AI Localization Community page here for more info!

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