The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
SemEval-2015 Task 10: Sentiment Analysis in Twitter
Open accessAbstract
In this paper, we describe the 2015 iteration of the SemEval shared task on Sentiment Analysis in Twitter.This was the most popular sentiment analysis shared task to date with more than 40 teams participating in each of the last three years.This year's shared task competition consisted of five sentiment prediction subtasks.Two were reruns from previous years: (A) sentiment expressed by a phrase in the context of a tweet, and (B) overall sentiment of a tweet.We further included three new subtasks asking to predict (C) the sentiment towards a topic in a single tweet, (D) the overall sentiment towards a topic in a set of tweets, and (E) the degree of prior polarity of a phrase.
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Cites
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A NEW MEASURE OF RANK CORRELATION
KENDALL, M. G. (1938) · Biometrika · doi:10.1093/biomet/30.1-2.81 · Cited by 7,269
Thumbs up?: sentiment classification using machine learning techniques
Pang, B., Lee, L., & Vaithyanathan, S. (2002) · Proceedings of the ACL-02 conference on Empirical methods in natural language processing - EMNLP '02 · doi:10.3115/1118693.1118704 · Cited by 7,024
Recognizing contextual polarity in phrase-level sentiment analysis
Wilson, T., Wiebe, J., & Hoffmann, P. (2005) · Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05 · doi:10.3115/1220575.1220619 · Cited by 3,345
Nonparametrics: Statistical Methods Based on Ranks
Mergenthaler, M. J., & Lehmann, E. L. (1979) · Technometrics · doi:10.2307/1268531 · Cited by 3,329
SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining
Baccianella, S., Esuli, A., & Sebastiani, F. (2010) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/2jktnrykui9s · Cited by 2,666
Thumbs up? Sentiment Classification using Machine Learning Techniques
Pang, B., Lee, L., & Vaithyanathan, S. (2002) · arXiv (Cornell University) · doi:10.48550/arxiv.cs/0205070 · Cited by 2,191
From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series
O'Connor, B., Balasubramanyan, R., Routledge, B., & Smith, N. (2010) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v4i1.14031 · Cited by 1,923
Annotating Expressions of Opinions and Emotions in Language
Wiebe, J., Wilson, T., & Cardie, C. (2005) · Language Resources and Evaluation · doi:10.1007/s10579-005-7880-9 · Cited by 1,755
Twitter power: Tweets as electronic word of mouth
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Cited by
Deep Convolution Neural Networks for Twitter Sentiment Analysis
Jianqiang, Z., Xiaolin, G., & Xuejun, Z. (2018) · IEEE Access · doi:10.1109/access.2017.2776930 · Cited by 482
Stance and Sentiment in Tweets
Mohammad, S. M., Sobhani, P., & Kiritchenko, S. (2017) · ACM Transactions on Internet Technology · doi:10.1145/3003433 · Cited by 449
Self-citationMohammad, S. M. (2016) · Emotion Measurement · doi:10.1016/b978-0-08-100508-8.00009-6 · Cited by 391
Self-citationSentiment analysis based on improved pre-trained word embeddings
Rezaeinia, S. M., Rahmani, R., Ghodsi, A., & Veisi, H. (2019) · Expert Systems with Applications · doi:10.1016/j.eswa.2018.08.044 · Cited by 325
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
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Metadata
- Authors
- Rosenthal, S., Nakov, P., Kiritchenko, S., Mohammad, S., Ritter, A., & Stoyanov, V.
- Venue
- Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)
- Published
- 2015
- Pages
- 451-463
- OpenAlex
- W2467186984
- Cited by
- 367
- References
- 23
- FWCI
- 45.07
- Type
- conference paper
- Language
- en
- Open access
- hybrid
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- Rosenthal, S., Nakov, P., Kiritchenko, S., Mohammad, S., Ritter, A., & Stoyanov, V. (2015). SemEval-2015 Task 10: Sentiment Analysis in Twitter. Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015). https://doi.org/10.18653/v1/s15-2078
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