SWASH: A Naive Bayes Classifier For Tweet Sentiment Identification
Proceedings Of The 9th International Workshop On Semantic Evaluation
This paper describes a sentiment classification system designed for SemEval-2015, Task 10, Subtask B. The system employs a constrained, supervised text categorization approach. Firstly, since thorough preprocessing of tweet data was shown to be effective in previous SemEval sentiment classification tasks, various preprocessessing steps were introduced to enhance the quality of lexical information. Secondly, a Naive Bayes classifier is used to detect tweet sentiment. The classifier is trained only on the training data provided by the task organizers. The system makes use of external human-generated lists of positive and negative words at several steps throughout classification. The system produced an overall F-score of 59.26 on the official test set.
9th International Workshop On Semantic Evaluation
June 4-5, 2015
Ruth W. Talbot , '15; C. Acheampong; and Richard H. Wicentowski.
"SWASH: A Naive Bayes Classifier For Tweet Sentiment Identification".
Proceedings Of The 9th International Workshop On Semantic Evaluation.