JOINT_FORCES: Unite Competing Sentiment Classifiers with Random Forest

摘要

In this paper, we describe how we created a meta-classifier to detect the message-level sentiment of tweets. We participated in SemEval-2014 Task 9B by combining the results of several existing classifiers using a random forest. The results of 5 other teams from the competition as well as from 7 general-purpose commercial classifiers were used to train the algorithm. This way, we were able to get a boost of up to 3.24 F_1 score points.