Jeffrey Heer

@jeffrey_heer · Seattle · joined 05 Feb 2011

UW Computer Science Professor. Data, visualization & interaction. he/him. @uwdata @uwdub @vega_vis ex-@trifacta

12 025Followers

785Following

1 412Posts total

68.6KViews on collected posts

Neueste Beiträge

Jeffrey Heer@jeffrey_heer15 Oct 2024

Congrats Dominik! 1.6K views · 19 likes · 0 reposts · 0 replies Open on X →

Jeffrey Heer@jeffrey_heer15 Oct 2024

Congratulations to IDL alum @domoritz for winning a VGTC Significant New Researcher award!! A premier honor for early career researchers in visualization! 9.5K views · 59 likes · 7 reposts · 7 replies Open on X →

Jeffrey Heer@jeffrey_heer18 Apr 2024

Excited to analyze text at the level of *interpretable concepts*, addressing many weaknesses of topic models we’ve found in the past - and with more control & revision by analysts. Also a fun collaboration between @uwdata and @StanfordHCI, led by the impressive @michelle123lam! 4.3K views · 27 likes · 4 reposts · 2 replies Open on X →

Jeffrey Heer@jeffrey_heer29 Feb 2024

@jeffrey_heer You can also build data apps with @Panel_org and Mosaic https://t.co/XLgZESAKbV https://t.co/ilN14Mn7S7 190 views · 3 likes · 0 reposts · 0 replies Open on X →

Jeffrey Heer@jeffrey_heer27 Feb 2024

@duckdb ...and you can easily deploy Mosaic-powered dashboards using Observable Framework: https://t.co/pIpNQGs1DN 2.9K views · 17 likes · 1 reposts · 0 replies Open on X →

Jeffrey Heer@jeffrey_heer27 Feb 2024

I've had fun playing with @observablehq Framework to deploy dashboards and web apps. Here's an example site integrating @uwdata Mosaic and @DuckDB for scalable visualization: https://t.co/BHKDsM11e5 https://t.co/SJHBx9nNEJ 17.5K views · 113 likes · 22 reposts · 3 replies Open on X →

Jeffrey Heer@jeffrey_heer27 Feb 2024

Mosaic uses @DuckDB - in-browser, on-server, or in a Jupyter kernel - and optimizes queries for fast, scalable visualization. https://t.co/n3J83hZtJD 2.2K views · 25 likes · 5 reposts · 1 replies Open on X →

Jeffrey Heer@jeffrey_heer27 Feb 2024

Interact with millions of data points in real-time with Mosaic, now with support for geospatial data. Exploring 1M taxi pickups and dropoffs in NYC: https://t.co/yoxhb96pT1 30.4K views · 339 likes · 39 reposts · 6 replies Open on X →

Jeffrey Heer@jeffrey_heer20 Aug 2019

Excited to share our #datavis notebook curriculum for learning visualization! Visual encoding, data transformation, interaction, maps, & more! Into Python? Here's Altair + Jupyter: https://t.co/LJ0QWE1in9 Prefer JavaScript? See Vega-Lite + @observablehq: https://t.co/1B1KkvOFct 0 views · 1.6K likes · 458 reposts · 13 replies Open on X →

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

30.4K27 Feb

2.2K

17.5K

2.9K

19029 Feb

4.3K18 Apr

9.5K15 Oct

1.6K

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

1.28%27 Feb

1.39%

0.79%

0.61%

1.58%29 Feb

0.77%18 Apr

0.81%15 Oct

1.18%

Reactions — likes, reposts, replies and quotes — divided by views.

What the audience does

Likes63.4%602 in total

Reposts8.2%78 in total

Replies2.0%19 in total

Quotes1.1%10 in total

Bookmarks25.3%240 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.

Neueste Beiträge

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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