Everyone’s story is a little different. Alyssa Fowers tracked her long-distance relationship in the context of the temperature between two locations and the travel to and from. Tags: relationships, temperature
Speaking of relationship timelines, Chris Lewis used texting history with his girlfriend after the first swipe on Bumble as the backdrop of their own story. A few 21k messages later, they’re engaged and live together. [Thanks, Chris] Tags: relationships, texting
Everyone's relationship timeline is a little different. This animation plays out real-life paths to marriage. Read More
We know that people are marrying later in life, but that's not the only shift. The whole relationship timeline is stretching. Read More
How do couples meet now and how has it changed over the years? Watch the rankings play out over six decades. Read More
"So how'd you two meet?" There's always a story, but the general ways people meet are usually similar. Here are the most common. Read More
Rosenfeld, et al. from Stanford University ran a survey in 2009 for a study on How Couples Meet and Stay Together. Dan Kopf and Youyou Zhou for Quartz used this dataset to estimate the probability that you will break up with your partner, given a few bits of information about your current relationship. The Stanford data page says a 2017 release is on the way. I’m curious how, if anything,...
Cartoonist Olivia de Recat illustrated the closeness over time for various relationships. Charming. Unfortunately, the print is sold out. Sad trombone. Tags: cartoon, Olivia de Recat, relationships
The Wall Street Journal highlighted a disagreement between data and business at Netflix. Ultimately, the business side “won.” However, maybe that’s the wrong framing. Roger Peng describes the differences between analysis and the full truth: There’s no evidence in the reporting that the content team didn’t believe the data or the analysis. It’s just that their fear of damaging a relationship with an actor overruled whatever desire they might have...
Roger Peng discusses the importance of managing the relationships between people — analyst, patron, subject matter expert, and audience — for a successful analysis: Human relationships are unstable, unpredictable, and inconsistent. Algorithms and statistical tools are predictable and in some cases, optimal. But for whatever reason, we have not yet been able to completely characterize all of the elements that make a successful data analysis in a “machine readable” format....