Some hashtags on the social image-sharing network Instagram have gone somewhat viral. The two that I use here are "#selfiesunday," which involves taking a photo of oneself on a Sunday and "#throwbackthursday" or "#tbt," which involves posting a picture of oneself from their past on a Thursday. Both these hashtags involve days of the week, and variations can be made such as "#selfietuesday" and "#throwbackwednesday." I took statistics from the Instagram search and made bar graphs for each of these phenomena covering all days of the week and "#tbt"-type acronyms.

The "#selfiesunday" analysis was quite straightforward. The code used follows:The variable "selfie" contains post counts for different hashtags for days of the week. Multiple addends account for variations in the hashtag such as "#selfiesundays" and "#selfiesundayyy." I accounted for all of these variations down to 5000 posts. The graph had to be plotted on a log scale because the original hashtag was much more popular than the variations, and a linear plot would have diminished the variations to an unreadable level. The resulting graph follows:

The "#throwbackthursday" graph was more complex for two reasons. One, I had to include both full hashtag names, such as "#throwbackthursday" and sometimes more-used acronyms, like "#tbt." Two, some acronyms, such as "#tbt," can represent two days of the week, Tuesday and Thursday in this case. The other scenario is "#tbs" for Sunday and Saturday. Also, I cannot account for alternate meanings of the acronym. I solved the first problem simply with a multi-series graph. For the second I used a weighted RandomChoice. The RandomChoice was weighted with the post counts of each of the two possible days, and I Table'ed it over the post count of the acronym. I then Count'ed the results and used them as the post counts for the acronyms. The code and graph follow:
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