How to Read in and Clean Your Facebook Data - I recently learned that you can download all of your Facebook data, so I decided to check it out and bring it into R. To access your data, go to Facebook, and click on the white down arrow in the upper-right corner. From there, select Settings, then, from the column on the left, &quot;Your Facebook Information.&quot; When you get the Facebook Information screen, select &quot;View&quot; next to &quot;Download Your Information.&quot; On this screen, you'll be able to select the kind of data you want, a date range, and format. I only wanted my posts, so under &quot;Your Information,&quot; I deselected everything but the first item on the list, &quot;Posts.&quot; (Note that this will still download all photos and videos you posted, so it will be a large file.) To make it easy to bring into R, I selected JSON under Format (the other option is HTML).After you click &quot;Create File,&quot; it will take a while to compile - you'll get an email when it's ready. You'll need to reenter your password when you go to download the file.The result is a Zip file, which contains folders for Posts, Photos, and Videos. Posts includes your own posts (on your and others' timelines) as well as posts from others on your timeline. And, of course, the file needed a bit of cleaning. Here's what I did.Since the post data is a JSON file, I need the jsonlite package to read it.setwd(&quot;C:/Users/slocatelli/Downloads/facebook-saralocatelli35/posts&quot;)library(jsonlite)FBposts %inner_join(get_sentiments(&quot;bing&quot;)) %__%acast(word ~ sentiment, value.var = &quot;n&quot;, fill = 0) %__%comparison.cloud(colors = c(&quot;red&quot;,&quot;blue&quot;), max.words = 100)## Joining, by = &quot;word&quot;Once again, a few words are likely being misclassified - regression and plot are both negatively-valenced, but I imagine I'm using them in the statistical sense instead of the negative sense. I also apparently use &quot;died&quot; or &quot;die&quot; but I suspect in the context of, &quot;I died laughing at this.&quot; And &quot;happy&quot; is huge, because it includes birthday wishes as well as instances where I talk about happiness. Some additional cleaning and exploration of the data is certainly needed. But that's enough to get started with this huge example of &quot;me-search.&quot;