You don’t know when the sad will fall. You can sometimes see it coming; like the water that falls on you from nowhere when you lie, it has some predictability. Unlike the water, it does not afford much opportunity for control, and you never know quite what to expect. When you see it coming, you can brace for impact; with practice, put on the happy face and soldier on.
That’s the idea, anyway.
Online platforms take different approaches to moderating — or not — the content that can be published or discovered through their platforms. I discovered today that some of the GIF search engines are censoring certain search terms. So I decided to poke a little more and see what is happening.
So, I won the NSF CAREER award. To say I’m excited about this would be an understatement — my first Ph.D student has support locked in, I get to actually do the work I’ve been building towards for years now, and we’re going to have a much better understanding of how recommender systems (mis)behave in response to their individual and social human contexts.
Over the years of teaching and research, I have gradually standardized the notation that I use for describing the math of recommender systems. This is the notation that I use in my classes, Joe Konstan and I have adopted for our MOOC, and that I use in most of my research papers. (And thanks to Joe for helping revise it to its current form.)
Fabric posters are great. You don't need a clumsy poster tube, just fold it up and put it in your suitcase.
We use Spoonflower for ours, and there are even instructions. But there are a few details that take some extra work to get right; I hope that this will guide you through them.