Abstract
We describe the submission of the SAP Research & Innovation team to the SemEval 2014 Task 9: Sentiment Analysis in Twitter. We challenged ourselves to develop a competitive sentiment analysis system within a very limited time frame. Our submission was developed in less than two days and achieved an F1 score of 77.26% for contextual polarity disambiguation and 55.47% for message polarity classification, which shows that rapid prototyping of sentiment analysis systems with reasonable accuracy is possible.
Cite
CITATION STYLE
Vij, A., Malhotra, N., Nandan, N., & Dahlmeier, D. (2014). SAP-RI: Twitter Sentiment Analysis in Two Days. In 8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings (pp. 522–526). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/s14-2091
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