Lmst

Stanford's Symbolic Systems Program is hiring a three-year lecturer position: https://academicjobsonline.org/ajo/program/29530

Big congratulations to Helena Vasconcelos on winning a 2025 CRA Outstanding Undergraduate Researcher Award! https://cra.org/about/awards/outstanding-undergraduate-researcher-award/

Coming very soon: #cscw2024 panel on "Is Human-AI Interaction CSCW?" alongside @asb, @jbigham, @andresmh, and Merrie Morris!

https://programs.sigchi.org/cscw/2024/program/content/179232

@andresmh @lindsay @julian yes, I think it’s also about everyone knowing that everyone has committed! I agree that providing the nudges for your friends would definitely work even better. “Hey Andrés, everyone wants to hear your hot take on…”

A reviewer called @lindsay's work "a rare example of a 'full stack' CSCW paper. It is an unusual system paper that feels theoretically motivated and is evaluated experimentally against a meaningful control."

Congratulations, @lindsay!

This paper argues that online spaces become ghost towns because it's too easy to lurk without contributing, and that asking people to regularly re-commit—or the incoming messages start getting muted—reverses the trend. arxiv.org/abs/2410.23267

It works! #cscw2024 paper by @lindsay

@bwaber Is the Snake Fight Portion of Your Thesis Defense not public knowledge? Best to be up front about these sorts of things.

You just got asked to review another paper; your third emoji is your review.

@pg @jbigham we can do a 1990s-style webring of endowed titles

Meme of four people aiming guns at each other's backs in a church. At the front is AUTHORS; aiming at them is REVIEWERS; aiming at them is SHERIDAN; aiming at them from the pews with a sniper rifle is TAPS

@andresmh Yes, the main difference is that the network is at best secondary and possibly just nonexistent. For example, you can follow on TikTok, but it's not a main driver of the FYP.

In theory, you can algorithmically rank any threaded design: spaces (Reddit), network (FB/Insta feed), or commons (TikTok FYP). Commons-based designs have few options beyond algorithmic ranking, though.

And yeah, when there's a bounded space, paid subscriptions to gain access is a clear metaphor.

@wollman @axz @karger Yup, it's in there! Though would love to hear any additional color you can add to the story.

Our argument is that design patterns largely cluster within cells of the Form-From design space. For example, threaded spaces commonly utilize upvotes, threaded networks often use resharing, and flat networks typically require posting on a "wall" rather than a central feed.

If you don't like our 2x3 space, there's also a full 62-dimension treatment in the appendix from our inductive process, as well as a set of 11 categories those fall into. They're more useful for fine-grained distinctions.

The Form-From model (left), the focus of our paper, is a distillation of a larger design space that we articulated and synthesized through our inductive process. We began with a review of systems and platforms to produce a large, maximal model that articulates 62 dimensions that we considered salient (right). We then iteratively grouped those dimensions hierarchically into 11 categories (middle), and finally selected and distilled them into two dimensions for Form-From.

Form-From asks two questions: (1) What is the principal shape, or form, of the content: either threaded or flat? (2)~From where or from whom one might receive content, ranging from spaces to networks to the commons?

Example screenshots including Slack, Reddit, Friendster, LiveJournal, Pinterest, TikTok, all split by the Form-From axes. (Order: flat to threaded, spaces to network to commons)

So just what is this thing? It's been a long time since CSCW introduced Johansen's Time-Space matrix, and at this point a vast majority of social media would fall into the different time - different place quadrant, making it not very productive as a design or theory tool.

Johansen's time-space matrix is a classic model of CSCW systems. It splits the design space by whether the people are interacting synchronously or asynchronously, and by whether people are in the same physical location. Most modern social media systems fall into the same ``different time--different place'' cell of these models.

One of my favorite little investigations was coding all the systems listed in a Wikipedia social media timeline (https://en.wikipedia.org/wiki/Timeline_of_social_media) as of when they launched with Form-From. The pattern weaves back and forth between flat systems and threaded systems over time.

Social media systems followed a pattern over time of moving from flat spaces (e.g., Talkomatic), to threaded spaces (e.g., Usenet), to flat networks (e.g., the original Facebook), to threaded networks (e.g., Reddit), to threaded commons (e.g., TikTok). This path does not describe every system---it describes an overall pattern.

What unifies, and what distinguishes, social media designs? Are all the Twitter spinoffs actually meaningfully different designs from each other? Form-From is a design space from @axz, myself, @karger, and Mark Ackerman that will appear at #cscw2024 https://arxiv.org/abs/2402.05388

$The Form-From model describes social media designs along two main dimensions: (1)~The \textit{form} or shape that the content takes, either flat as in a chatroom or threaded as in individual posts with linked comments, and (2)~\textit{from} where a user receives content, as from spaces such as channels, from networks such as a friend graph, or from a platform-wide commons such as an algorithmic For You page. For simplicity, examples in this figure are coded as of their design at their initial launch.$

@bwaber :)

We're looking for a broad set of scholars, ranging across qualitative and critical studies, quantitative data science or experimental research, policy, social computing platform design and deployment, and AI. Apply by February 20.

If you're interested in AI and social media, apply for this postdoc position at
Stanford: https://hci.stanford.edu/postdoc.php

Work with faculty including @Angelec (Communication), Jeanne Tsai (Psych), Jeff Hancock (Communication), @jugander (MS&E), myself (CS), Nate Persily (Law), @RobbWiller (Sociology, Psychology, Business), and Tatsu Hashimoto (CS). Postdocs get joint mentorship by a pair of faculty.

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