Strava tweets II: after dinner rides and Sunday morning rides

12 April 2015

The other day I posted an article about using Strava tweets to analyse road cycling patterns. I plan to do some more analysis on this but first I wanted to take another look at the time at which tweets are posted. Below is a chart that shows the number of Strava tweets per hour of the day.

Two things stand out: on weekdays, there’s an after-dinner peak, and on Sundays, many trips are finished before lunch. The pattern suggests that people tend to tweet pretty quickly after they finish their ride. This in turn seems to suggest that post times may well be a meaningful indicator of the time at which rides take place.

Gender

I used a variant of this script to determine the gender of people who tweeted their Strava rides, based on the first name of their Twitter screen name. According to the results, 9.7% are women. This is more than the 5.5% women in the SWOV survey among Dutch road cyclists, but then again people who use Strava (and tweet about it) are probably more likely to be young and young road cyclists more likely to be women.

For women the median distance of rides is 48km; for men 54km. The difference doesn’t appear very large.

In the chart above, you can select to see data for women instead of all riders (note that the scale changes). The main difference seems to be that for women, there’s much less of an after-dinner peak on weekdays. Perhaps something to do with the fact that women are less likely to have full-time jobs. But the numbers are relatively small so perhaps one shouldn’t read too much into it.

12 April 2015 | Categories: cycling, d3js, data, python, strava