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SemEval-2014 Task 9: Sentiment Analysis in Twitter
Open accessAbstract
We describe the Sentiment Analysis in Twitter task, ran as part of SemEval-2014.It is a continuation of the last year's task that ran successfully as part of SemEval-2013.As in 2013, this was the most popular SemEval task; a total of 46 teams contributed 27 submissions for subtask A (21 teams) and 50 submissions for subtask B (44 teams).This year, we introduced three new test sets: (i) regular tweets, (ii) sarcastic tweets, and (iii) LiveJournal sentences.We further tested on (iv) 2013 tweets, and (v) 2013 SMS messages.The highest F1score on (i) was achieved by NRC-Canada at 86.63 for subtask A and by TeamX at 70.96 for subtask B.
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Cited by
Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification
Tang, D., Wei, F., Yang, N., Zhou, M., Liu, T., & Qin, B. (2014) · Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.3115/v1/p14-1146 · Cited by 1,181
Mohammad, S. M. (2016) · Emotion Measurement · doi:10.1016/b978-0-08-100508-8.00009-6 · Cited by 391
SemEval-2015 Task 10: Sentiment Analysis in Twitter
Rosenthal, S., Nakov, P., Kiritchenko, S., Mohammad, S., Ritter, A., & Stoyanov, V. (2015) · Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015) · doi:10.18653/v1/s15-2078 · Cited by 367
Self-citationA Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks
Poria, S., Cambria, E., Hazarika, D., & Vij, P. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1610.08815 · Cited by 292
Detecting Stance in Tweets And Analyzing its Interaction with Sentiment
Sobhani, P., Mohammad, S., & Kiritchenko, S. (2016) · Proceedings of the Fifth Joint Conference on Lexical and Computational Semantics · doi:10.18653/v1/s16-2021 · Cited by 130
Metadata
- Authors
- Rosenthal, S., Ritter, A., Nakov, P., & Stoyanov, V.
- Venue
- Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)
- Published
- 2014
- Pages
- 73-80
- OpenAlex
- W2250243742
- Cited by
- 617
- References
- 0
- FWCI
- 61.66
- Type
- conference paper
- Language
- en
- Open access
- hybrid
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- Rosenthal, S., Ritter, A., Nakov, P., & Stoyanov, V. (2014). SemEval-2014 Task 9: Sentiment Analysis in Twitter. Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014). https://doi.org/10.3115/v1/s14-2009
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