There have been a number of posts here on ProfHacker about using Twitter, particularly around archiving tweets. Our favorite method has been
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There have been a number of posts here on ProfHacker about using Twitter, particularly around archiving tweets. Our favorite method has been Martin Hawksey’s free TAGS template for Google Sheets. But, there may be a situation when you want a quick analysis of activity around a certain hashtag or term (trending or otherwise) without the trouble of setting up a permanent archive.
Enter a new tool developed by Knight Lab out of Northwestern, the same folks who brought us the popular timeline.js platform, which Amy has written about, as well as a number of other digital storytelling tools. Their most recent tool is twXplorer, which allows you search for a specific hashtag or term, giving you the most recent 500 tweets along with some basic analysis of the content found therein.
I decided to search #RIPTwitter (a popular hashtag recently due to the changes Twitter has been proposing) to show what the tool is capable of doing. You can quickly see the most recent tweets, as well as the hashtags, related terms, and links. You (and your students) can get a quick snapshot of what is going on in this particular hashtag. I also like that you can search in 13 different languages, allowing for comparisons of how a hashtag or trend is being discussed in (theoretically) different parts of the world. You can also take a snapshot of your search results and consult with them later, or do a comparison with later search results.
Now, there are some shortcomings as well. This isn’t a live archive, and because of the Twitter API, it’s limited to how far back it will search, as well as how many tweets it can retrieve. However, if your goal is to quickly start a conversation around social media trends or how an event is evolving, or to get students to start to see the potential of doing these kinds of exercises, then this is a great, free and easy to use tool.
Have you used twXplorer? What other ways could you see using this tool? Are there other Twitter analysis tools you’ve found helpful? Please share in the comments.
