Michael pointed me to a story about how Stanford scientists put free text-analysis tool on the web. The tool allows you to pass a text (or a Twitter hashtag) to an existing classifier like the Twitter Sentiment classifier. It then gives you a interactive graph like the one above (which shows tweets about #INKEWhistler14 over time.) You can upload your own datasets to analyze and also create your own classifiers. The system saves classifiers for others to try.
I’m impressed at how this tool lets people understand classification and sentiment analysis easily through Twitter classifications. The graph, however, takes a bit of reading – in fact, I’m not sure I understand it. When there are no tweets the bars go stable, and then when there is activity the negative bar seems to go both up and down.