IOA: Improving SVM Based Sentiment Classification Through Post Processing

This paper describes our systems for expression-level and message-level sentiment analysis -two subtasks of SemEval-2015 Task 10 on sentiment analysis in Twitter.First we built two baseline systems for the two subtasks using SVM with a variety of features.Then we improved the systems through model iteration and probability-output weighting respectively.Our submissions are ranked the 3rd and 2nd among eleven teams on the 2015 test set and progress test set in subtask A and the 7th and 4th among 40 teams on the two test sets respectively in subtask B.