tweetindex
EN

Fact Protocol

@FactProtocol · Global · joined 30 May 2021

A not-for-profit deep tech research and innovation ecosystem focused on AI integrity and trustworthy information: provenance tools & programs.

77 078Followers
785Following
13 053Posts total
691.4KViews on collected posts

Latest posts

India’s official Q1 GDP is 7.8%. The 2.6% figure mixes two different statistical series. This essay explains the new method and what the criticism actually covers. https://t.co/585AwxOe6B 1.5K views · 6 likes · 4 reposts · 1 replies Open on X →
📄 Paper: https://t.co/VdSspt7cqh 295 views · 2 likes · 0 reposts · 0 replies Open on X →
He wore a fake Rolex. Nobody questioned it. When status is already high and clear, observers often assume it is genuine. The social context does more than the material signal. A new working paper by our founder @MohithAgadi explores this idea through countersignalling and https 191.9K views · 9 likes · 0 reposts · 2 replies Open on X →
Read working paper: https://t.co/iqmFbGDva3 596 views · 1 likes · 0 reposts · 0 replies Open on X →
Access Dilution (n.) When the same membership, donation, or loyalty status buys less recognition, exclusivity, and meaningful access as more people join. Same formal access. Lower real value. https://t.co/jmugkTDZNM 477.1K views · 45 likes · 3 reposts · 1 replies Open on X →
"Access Dilution" - Definition on Urban Dictionary: https://t.co/LTBbjDmTDV 1.8K views · 3 likes · 0 reposts · 2 replies Open on X →
@FactProtocol @MohithAgadi Interesting concept about contribution purchasing power. 13 views · 2 likes · 0 reposts · 0 replies Open on X →
https://t.co/g0zOYvRunO https://t.co/PMMo8VDlqD
213 views · 2 likes · 0 reposts · 0 replies Open on X →
New working paper authored by our founder @MohithAgadi is now live on SSRN: Access Dilution in Contribution Economies: Scarcity, Scale, and the Erosion of Contribution Purchasing Power Introduces the Contribution Purchasing Power (CPP) model to explain why value often declines 1.8K views · 9 likes · 0 reposts · 3 replies Open on X →
🔔 CETaS at The Alan Turing Institute in the UK cited @FactProtocol in its research report titled "AI-Enabled Influence Operations: Safeguarding Future Elections." @turinginst https://t.co/HkYVrQvnuV 16.1K views · 12 likes · 2 reposts · 2 replies Open on X →

Against accounts of the same size

9 posts from the last 90 days, next to the 10K–100K follower range. below its peers on both reach and engagement.

Median views1 456this account965median for 10K–100K
Reach, %1.89%this account3.33%median for 10K–100K
Engagement, %0.68%this account1.85%median for 10K–100K
MetricThis accountMedian for 10K–100KRatio
Median views per post1 4569651.51×
Reach (views ÷ followers)1.89%3.33%0.57×
Engagement rate0.68%1.85%0.37×

Others in this range →   Compare with another account →   How these benchmarks are built →

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

16.1K5 Sep
1.8K3 Aug
213
137 Aug
1.8K
477.1K9 Aug
596
191.9K13 Aug
295
1.5K3 Sep

Last 10 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.10%5 Sep
0.70%3 Aug
0.94%
15.38%7 Aug
0.27%
0.01%9 Aug
0.17%
0.01%13 Aug
0.68%
0.76%3 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.85%.

What the audience does

Likes74.0%91 in total
Reposts7.3%9 in total
Replies8.9%11 in total
Quotes0.8%1 in total
Bookmarks8.9%11 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.

Similar accounts