I ended up collecting the dates and tags on posts. I set up a spreadsheet with the tag names on the top, and the dates going down of all of the posts that were tagged with that tag. These tags included not only the ones in the menu, but also categories that the author included even though they were not actually on the menu page. As I collected my data, I discovered that there were some menu tags that did not have posts (at least since Jan 2015 (this is the date I decided on to go back to for my data collection)). These particular tags I will mention briefly, but since they do not seem to be incredibly important (at least important enough to blog about (which is what this research question is studying, so therefore they are not important enough for my purposes)) I will focus primarily on the tags that do have posts since Jan 2015, and especially focus on how many posts each tag has and how that shows what seems to be important for this community.
Since, for the purposes of my research question, it seems that the amount of posts in each tag or category corresponds to how popular that particular topic is to the community, I will use the visualizations to show the correlation between the popularity of each tag to the amount of times it has appeared (and its frequency). There are multiple ways to show the relationship between the frequency (shown by the dates), and each of the tags. Since I am looking for the popularity in correlation between each of the tags, I will probably do something along the lines of larger or smaller bubbles for each tag depending on how many posts they have, as well as perhaps month bubbles that contain the tags in either larger or smaller font depending on how many posts there are in that tag, I might also make a slightly more comedic visualization that would show the correlation between each post or tag and if it relates only to military wives or if it could also apply to civilian wives.