This week's Effect+Affect: What can dinner parties teach us about dataviz 📊? Thanks to ensemble perception, your brain is weirdly good at parallel processing faces, grass, and zillions of lines on charts.
| Site | https://3iap.com |
| Location | Raleigh, NC |
Eli Holder
- 185 Followers
- 190 Following
- 83 Posts
Maker / geek! ❤️ Data, design, dataviz, product, systems, clojure, feedback & mischief. He/him.
Ensemble perception is part of the power behind strikingly detailed visualization's like Fernanda Viegas + Martin Wattenberg's wind maps, Periscopic's US Gun Deaths, and Nadieh Bremer's Wars.. as well as more utilitarian charts like jitter plots.
Is Taylor Swift a CIA psyop? No? Don't think so? What if you hear about it four more times? In our second post for Effect+Affect, Gabby and I unpack how "Truth by Repetition" can make absurd information seem more plausible and what it means for data communication.
https://effaff.com/repeat-after-me-truth-by-repetition-effect/
Our first post is here. We look at how contrast effects in information design can convince college students that a disease with an 11% risk is more likely than one with 12% risk.
How did this happen? What does it mean for dataviz design?
...and overstate _everything_ in a way that's academically questionable, but hopefully exciting? And, of course, we'll invite the research community to call us on our bullshit and share any discussions that pop up as we go! Hooray science!
...something more approachable. So every week(ish) we'll pull one of our favorite studies from the stack, unpack the findings and relate them back to data design, and maybe turn some of the results into a hopefully not-too-reductive postcard.
Along the way we'll sensationalize, editorialize...
Gabby Merite and I are doing a newsletter! We're calling it Effect+Affect. You can sign up at https://effaff.com
The idea: We think data design research is super cool. We use it in our own design work. But academic papers are Zzz and intimidating. So we're attempting to translate our favorites into...
New Nightingale post!
Political polls in the news are like reality TV for people who like spreadsheets. They’re a fun guilty-pleasure, but they’re not exactly a public service and shouldn’t be taken too seriously. They’re also low-key toxic.
In this research roundup, I unpack three recent dataviz 📊 studies and consider how cliches in political data journalism can subtly undermine the democratic process.
https://nightingaledvs.com/divisive-dataviz-how-political-data-journalism-divides-our-democracy/
Group-vs-group comparisons like these can be sketchy in other ways too, particularly for race / ethnicity.
Susana Peinado + others at the CDC did an _epic_ review of these social comparison effects. Absolutely worth a look for health / equity 📊 designers:
https://www.frontiersin.org/articles/10.3389/fcomm.2020.539174/full
Effectively Communicating About HIV and Other Health Disparities: Findings From a Literature Review and Future Directions
Despite significant progress in the prevention and treatment of HIV, disparities in rates of infection remain among key groups in the United States, including blacks and African Americans; Hispanics/Latinos; and men who have sex with men (MSM). The U.S. Department of Health and Human Services' initiative, Ending the HIV Epidemic: A Plan for America, calls for addressing HIV-related disparities and reducing stigma and discrimination associated with HIV. The goal of this literature review was to identify approaches for effectively communicating about health disparities across the HIV care continuum. We reviewed the literature to investigate strategies used to communicate health disparities and to identify potential unintended adverse effects resulting from this messaging. Messages about health disparities often target subgroups at higher risk and can be framed in a variety of ways (e.g., social comparison, progress, impact, etiological). Studies have examined the effects of message framing on the risk perceptions, emotional reactions, and behaviors of individuals exposed to the messaging. The evidence points to several potential unintended adverse effects of using social comparison framing and individual responsibility framing to communicate about health disparities, and visual images and exemplars to target messages to higher-risk subgroups. There is not yet a clear evidence-based approach for communicating about health disparities and avoiding potential unintended effects....
These contrast effects are a big deal for equity-viz. Disaggregating health risks by race/age/etc might backfire similarly. e.g. early Covid news reports, highlighting risk disparities for essential workers or older people, may have convinced everyone else that the pandemic wasn't their problem.