I’d like to enlist your help in a project we have been creating at the USC Annenberg Innovation Lab . We have built an analytics tool to track sentiment around the two candidates using Twitter as the data feed. So we take in every tweet about the candidates and our language-ware reads the tweets and creates a score from 1-100, positive or negative. In the Presidential Debate this Wednesday we will probably be reading and analyzing up to 1000 tweets per second. Ideally our real time sentiment analysis will act like a million person focus group on the debate.This work is similar to the analyses we’ve done over the past 18 months on pop culture events like the Oscars, Summer Blockbusters, Fashion Week trends, and sporting events such as the World Series and Super Bowl.
So here is where we need help. Computers, as you might imagine, are not great at detecting sarcasm. Though advances in software and cognitive computing are helping us make great progress.When we first started this project I remember a tweet, “I’m so happy Michelle Bachmann has thrown her tin foil hat in the ring”. The computer thought that was a positive sentiment towards Bachmann, until a human student corrected it. We have built a human annotation page into the dashboard where you can correct any tweet you think has been mis-scored. From the main page of the site, click “Go to Tweets/annotation page”. There you will see a sampling of the latest tweets and their score. Click on any given tweet and you will be taken to an annotation page where you can manually correct the computer. Obviously the more people who do this, the better the outcome.
One last note. Obviously as you read some of the most negative tweets you will be appalled at what passes for political dialogue in the age of Twitter. We surmise that because many people tweet anonymously, they feel free to speak in the most hateful language. As you will see, most people tweet against a candidate rather than for a candidate. It says something about the psychology of Twitter, but I’m not sure just what it means for an digital democracy.
We’re learning quite a bit through this project and others about how analytics technologies can be applied to Big Data to understand and predict trends. Thanks in advance for your help.