I had the pleasure of visiting the Facebook data science team last week, and we spent some time chatting about visual communication, something they care as much about as I do. Solomon reported about our conversation in this blog post. One topic is stacked bar charts, which are useful in limited situations, such as when the categorical variable has two or three levels.
Solomon used stacked bars in his fascinating post about how candidates from the two political parties are using Facebook messages in the run-up to mid-term elections. Be sure to read about it here. This is an example of good data journalism in which the outcomes of the analysis are presented simply, hiding the amount of technical work that went into its production.
This stacked bar chart is effective at pointing out the differences in the types of messages being sent out by party:
I do have one question, which is the placement of the 50-percent line. The line is very important to this chart, and I like the way it looks. When the line sits at 50 percent, it implies that the Republican and Democratic candidates were issuing about equal numbers of Facebook messages. If the share of total messages is not 50/50, then the reference line should sit elsewhere.
They later split the races by tosses-up versus uncompetitive, and use confidence intervals to communicate both the expected rate and the uncertainty of the estimate. The uncertainty bars in effect tell readers that there are many more uncompetitive elections than tosses-up.
The choice of the chart form is fine. But it makes me pull out my Tufte book. The data-ink ratio on this chart needs a little help. The gridlines can go. Even the 250 label on the x-axis can go. I might even go with just labelling the midpoints.
Lastly, this next chart is enlightening. Seems like older adults are much more likely to comment and/or like such political messages; men are more likely to comment while women are more likely to like. The small-multiples format helps us grasp the three-way analysis without much suffering.