World Bank Data

@worldbankdata · joined 16 Oct 2010

The Development Data Group unlocks the value of #data for development. Follow us for #opendata news, stories & #dataviz. More: https://t.co/SYIZiT3UuE

82 863Followers

413Following

22 710Posts total

74.9KViews on collected posts

โพสต์ล่าสุด

World Bank Data@worldbankdata22 Sep

US$30 million a year. That’s what Guinea-Bissau could gain from making two agricultural value chains work better. What is making this chain less effective and more challenging?: https://t.co/m846kWiIII https://t.co/yumzMd8aeu

253 views · 1 likes · 0 reposts · 0 replies Open on X →

World Bank Data@worldbankdata22 Sep

Administrative data hold potential for better statistics & policy. In our upcoming LET'S TALK DATA event, former UK Office for National Statistics Chief Data Officer Roberto Pitea shares practical lessons on making government data sharing work. Register: https://t.co/jB4qTjAzAv

610 views · 3 likes · 1 reposts · 0 replies Open on X →

World Bank Data@worldbankdata21 Sep

Did you know that data sharing initiatives can generate an estimated US$5 in social returns for every dollar invested. But realizing that value takes more than APIs and platforms. Check our five-part roadmap for turning government data into public value: https://t.co/L1GHnK03rm

1.6K views · 18 likes · 3 reposts · 2 replies Open on X →

World Bank Data@worldbankdata21 Sep

Can mobile phone records help identify people living in poverty? Evidence from Afghanistan, Côte d'Ivoire, Malawi, and Togo suggests they can — especially when the goal is to identify chronic poverty and vulnerability where survey data are limited: https://t.co/h6VrxJEIOV https

1.4K views · 11 likes · 2 reposts · 0 replies Open on X →

World Bank Data@worldbankdata9 Jul

The world's income map has shifted since 1987. Low-income countries went from 30% to 11% High-income economies went from 25% to 41% Learn more with the recently launched 2026-2027 @WorldBankGroup Country Income Classifications: https://t.co/mqfXBmeQot https://t.co/H2w9NYcFsH

71.1K views · 155 likes · 70 reposts · 12 replies Open on X →

เทียบกับบัญชีขนาดเดียวกัน

4 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง 10K–100K ผู้ติดตาม ต่ำกว่าบัญชีรุ่นเดียวกันทั้งการเข้าถึงและการมีส่วนร่วม.

ยอดดูมัธยฐาน1 018บัญชีนี้924ค่ามัธยฐานของ 10K–100K

การเข้าถึง, %1.23%บัญชีนี้3.62%ค่ามัธยฐานของ 10K–100K

การมีส่วนร่วม, %0.78%บัญชีนี้1.52%ค่ามัธยฐานของ 10K–100K

ตัวชี้วัด	บัญชีนี้	ค่ามัธยฐานของ 10K–100K	อัตราส่วน
ยอดดูมัธยฐานต่อโพสต์	1 018	924	1.10×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)	1.23%	3.62%	0.34×
อัตราการมีส่วนร่วม	0.78%	1.52%	0.52×

บัญชีอื่นในช่วงนี้ → เปรียบเทียบกับบัญชีอื่น → ค่าอ้างอิงเหล่านี้คำนวณอย่างไร →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

71.1K9 Jul

1.4K21 Sep

1.6K

61022 Sep

253

Last 5 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.34%9 Jul

0.91%21 Sep

1.60%

0.66%22 Sep

0.40%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes52.8%188 in total

Reposts21.3%76 in total

Replies3.9%14 in total

Quotes2.8%10 in total

Bookmarks19.1%68 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.