The predictive power of tweets: an exploratory study
Summary
We describe a system that estimates when an event is going to happen from a
stream of microtexts on Twitter referring to that event. Using a Twitter archive of
60 known football events, this problem is transferred into a classiffcation problem.
Different training procedures were followed, such as varying the training data and
hierarchical classiffcation. The best performing method was on average 52.3 hours
off, and especially the tweets that referred to an event that was still far away
appeared to be hard to predict. Comparing the performance of the system to
the performance of humans on the same task, it appeared that there is room for
improvement for the system.