Facebook experiments – Using a technical glitch to nudge user’s behaviour, maybe

For a couple of weeks’ I would log onto Facebook and two of my friend’s chat windows would appear. I would close them both down, mindlessly browse the News Feed then switch to something more interesting, with turns out to be anything. The next day I would repeat the process – the same two chat windows popped-up, unprompted by any messages from my friends. I’m not an active Facebook user, yet this was irritating. I half-heartedly Googled for a solution but gave up because only half my heart was invested.

Earlier this week I logged on and the issue appeared to have resolved itself. Yesterday I received a message from one of these Facebook friends via my Messenger app. This friend asked if I was free for coffee on the weekend. I am and wrote back. I’ve only met this person twice in real-life occasions spread over years, but the last time we spoke (about a month ago) we got on well and we swapped a few Facebook messages after. I’m glad she arranged a meet-up in the real-world.

Then my paranoia set in. Was this apparent chat window glitch a cleverly disguised Facebook experiment? We know that Facebook runs experiments. What if Facebook sampled its users, popped-up some chat windows, then tracked how many people engaged in further chats? Did the display of the glitch windows cause a lift in chat-engagement? With some text analysis, did it result in plans for a real-world meet-up?

I barely see these two friends – one is living in regional NSW and the glitchy chat window is not compelling enough for me to visit her where there is no city. I’ll check with my real-life coffee friend if she received my chat window as a pop-up and whether it nudged her to reach out. If so, cool. The potential for Facebook to run different experiments is expansive and creative – using glitches as a guise, what else can/do they do? As a former research scientist, I respect it and am envious that they can tweak the Facebook world, sit back and watch users shift their behaviour.

FODMAPs 01 – Data collection

There’s something in my diet that ain’t sitting right. It makes me feel bloated, fatigued and just damn uncomfortable. It’s been like this for years, though it’s been tolerable. Recently I went to a dietitian/nutritionist to learn more about what I should and should not shove down my mouth.

After describing my general diet, I received advice that will sound obvious to most. I need more fruits, vegetables, fibre and water.
“How many fruits and veges am I supposed to eat?”, I asked.
“Two serves of fruit, three serves of vegetables a day.”
“Oh, so the recommendation hasn’t changed since kindergarten?”. I was really hoping that it had been scaled back to two fruits per day. Or one magic fruit pill.

I took the advice as best as I could manage (who has time to eat five serves of vegetables a day? Takes so long to chew). There were marginal improvements. I felt less bloated and fatigued, so my decisions were leading me in the right direction. Similarly, I had stopped drinking coffee back in March and noted improvements. Each dietary change added an improvement.

However, I still feel uncomfortable. Years ago I attempted to rectify my dietary issues with data. I recorded what foods I was eating and what symptoms I felt day to day with the intention to analyse my way to a remedy. I planned to “net” what foods caused upset. I never got around to the analysis.

I’m getting around to it now. I have the right tools.

The nutritionist said I should try a low FODMAP diet. FODMAPs are a group of carbohydrate that are poorly digested. After a FODMAP diet of at least 6 weeks, I’ll gradually reintroduce different FODMAP groups and note my tolerance. I can identify my problem foods then avoid them. But not ice cream. If ice cream is a problem food, I’ll just take lactase beforehand.

I need an app that collects my food intake. I’ve used myfitnesspal in the past. When I Googled for instructions on exporting my data, I couldn’t find a clear guide, or it was a paid option. I can log foods with the Fitbit app, however retrieving the data is also not easy. The Fitbit R scraper I use does not retrieve food data. I would have to access my data via an API.

Instead I’ll use the Memento Database app. Memento Database allows users to customise fields for data capture then easily export the data as CSV. My “Food” library captures the foods or ingredients I consume with the current datetime captured upon entry. I will use short general labels for foods and ingredients as possible since I’d like to group the foods for analysis.

My “Symptoms” library captures a symptom with the datetime. I used to enter detailed symptom descriptions. I want to keep it brief. I'll include feelings of "Fatigue" or feeling "Bloated". The symptoms will be placed in a single-choice list. I expect that these symptoms will decrease as I persist with the lower FODMAP diet. The symptoms will increase when I reintroduce the problem FODMAP groups. Ice cream will totally be fine. Totally.

I will combine this food and symptom data with Fitbit data, namely calories burned, weight and sleep. I’m curious to see if my weight changes with the diet (assuming little change in the calories burned day-to-day) or if my sleep improves. 

In say, 6 weeks’ time, I’ll have data to wrangle then analyse.

Building plots with ggraptR’s code gen

Building plots for R newbies is a challenge, even for R not-so-newbies like myself. Why write code when it can be generated for you?

I have put my hand up to volunteer towards an R visualisation package called ggraptR. ggraptR allows interactive data visualisation via a web browser GUI (demonstrated in a previous post using my Fitbit data). The latest Github version (as of 13^th September 2016) contains a plotting code generation feature. Let’s take it for a spin!

I have a rather simple data frame called ""dfGroup" that contains the number of Breaking Bad episodes each writer wrote. I want to create a horizontal bar plot with the “Count” on the x-axis and “Writer” on the y-axis. The writers will be ordered from most episodes written (with Mr Vince Gillian at the top) to least (bottom). It will have an awesome title and awesomely-labelled axis. The bars will be green. Breaking Bad green.

Before code gen, I would Google “R horizontal bar ggplot with ordered bars”, copy paste code then adjust it by adding more code. The ggraptR approach begins with installing and loading the latest build:

devtools::install_github('cargomoose/raptR', force = TRUE)

library("ggraptR")

Launch ggraptR with ggraptR().

A web browser will launch. Under “Choose a dataset” I selected my dfGroup data frame. Plot Type is “Bar”. The selected X axis is “Writer” and the Y is “Count”. “Flip X and Y coordinates” is checked. And voilà – instant horizontal bar plot.

Notice the “Generate Plot Code” button highlighted in red. Clicking on said button – a floating window with code will appear.

I copied and pasted the code in an R script. I tidied the code a bit as shown below. Running the code (with dfGroup in the environment) will produce the plot as displayed with ggraptR. 

With a tiny bit of modifying – adding a title, changing the axis titles and filling in the bars with Breaking Bad green, we have the following:

One last thing – the bars are not ordered. Currently the bars cannot be ordered with ggraptR. I can reorder the bars using the reorder function on the dfGroup data frame. Back in RStudio, I run the following:

dfGroup$Writer <- reorder(dfGroup$Writer, dfGroup$Count)

then execute the modified code above and we have plotting success!

Using ggraptR you can quickly build a plot, use code gen to copy the code then modify it as desired. Happy plotting!