Suproteem Sarkar ✓

@SuproteemSarkar

Assistant Professor @UChicago

1 015Followers

274Following

82Posts total

98KViews on collected posts

Against accounts of the same size

6 posts from the last 90 days, next to the under 10K follower range. shown widely, but few of those viewers react.

Median views7 041this account2 700median for under 10K

Reach, %693.69%this account176.06%median for under 10K

Engagement, %0.60%this account1.57%median for under 10K

Metric	This account	Median for under 10K	Ratio
Median views per post	7 041	2 700	2.61×
Reach (views ÷ followers)	6.9× audience	176.06%	3.94×
Engagement rate	0.60%	1.57%	0.38×

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

9.7K4 Sep

66.1K

6.6K

7.5K

5.5K

2.7K

Last 6 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.80%4 Sep

0.68%

0.41%

0.52%

0.48%

1.88%

Reactions — likes, reposts, replies and quotes — divided by views. Median for under 10K accounts is 1.57%.

What the audience does

Likes56.3%590 in total

Reposts4.6%48 in total

Replies2.2%23 in total

Quotes1.0%11 in total

Bookmarks35.9%376 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.

Latest posts

@SuproteemSarkar Out of all things that do not make sense, this does not make sense the most. 2.7K views · 50 likes · 0 reposts · 1 replies 04 Sep 2026 more information here: https://t.co/1FbPsGONpc comments are very welcome! 5.5K views · 24 likes · 2 reposts · 0 replies 04 Sep 2026 coherence varies quite a lot across models, by around two orders of magnitude. higher coherence is also associated with higher accuracy https://t.co/wyY0pIjnkg 7.5K views · 36 likes · 2 reposts · 1 replies 04 Sep 2026 forecasts are more incoherent when there are more logical relations between events, for example joint distributions versus marginal distributions also when we add context like “I’m feeling really optimistic about this,” or even “I had coffee this morning, by the way” https://t.c 6.6K views · 22 likes · 3 reposts · 2 replies 04 Sep 2026 suppose you ask a language model the probability it will rain tomorrow. then you ask the probability it will not rain tomorrow whatever happens tomorrow, those two probabilities should sum to one but suppose the model generates P(rain) = 0.7 and P(no rain) = 0.2 https://t.co/Qa 66.1K views · 389 likes · 34 reposts · 18 replies 04 Sep 2026 in a new paper with Isaiah Andrews, we evaluate probabilistic coherence in language model forecasts we build a forecasting environment for models from historical stock returns. we then measure incoherence through the profit you can make by arbitraging a model’s forecasts https:/ 9.7K views · 69 likes · 7 reposts · 1 replies 04 Sep 2026