Publication:
KUNLPLab: sentiment analysis on twitter data

Placeholder

School / College / Institute

Organizational Unit

Program

KU Authors

Co-Authors

Publication Date

Language

Embargo Status

Journal Title

Journal ISSN

Volume Title

Alternative Title

Abstract

This paper presents the system submitted by KUNLPLab for SemEval-2014 Task9 - Subtask B: Message Polarity on Twitter data. Lexicon features and bag-of-words features are mainly used to represent the datasets. We trained a logistic regression classifier and got an accuracy of 6% increase from the baseline feature representation. The effect of pre-processing on the classifier’s accuracy is also discussed in this work. © 8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings.

Source

Publisher

Association for Computational Linguistics (ACL)

Subject

Engineering, Computer Science, Artificial intelligence

Citation

Has Part

Source

8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings

Book Series Title

Edition

DOI

item.page.datauri

Rights

Copyrights Note

Endorsement

Review

Supplemented By

Referenced By

0

Views

0

Downloads