The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Learning to identify emotions in text
Open accessAbstract
This paper describes experiments concerned with the automatic analysis of emotions in text. We describe the construction of a large data set annotated for six basic emotions: ANGER, DISGUST, FEAR, JOY, SADNESS and SURPRISE, and we propose and evaluate several knowledge-based and corpusbased methods for the automatic identification of these emotions in text.
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Cites
WordNet: An Electronic Lexical Database
Kilgarriff, A., & Fellbaum, C. (2000) · Language · doi:10.2307/417141 · Cited by 11,464
Picard, R. W. (1997) · MIT Press · doi:10.7551/mitpress/1140.001.0001 · Cited by 7,382
WordNet: An Electronic Lexical Database
(1998) · The MIT Press eBooks · doi:10.7551/mitpress/7287.001.0001 · Cited by 4,857
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
Pang, B., & Lee, L. (2004) · Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics - ACL '04 · doi:10.3115/1218955.1218990 · Cited by 3,301
SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining
Esuli, A., & Sebastiani, F. (2006) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/54vo5wjya4cw · Cited by 2,480
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
Measuring praise and criticism: Inference of semantic orientation from association
Turney, P. D., & Littman, M. L. (2003) · ACM Transactions on Information Systems · doi:10.1145/944012.944013 · Cited by 1,502
WordNet Affect: an Affective Extension of WordNet
Strapparava, C., & Valitutti, A. (2004) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/2yctm9q26ar4 · Cited by 1,384
Self-citationAn Electronic Lexical Database
Fellbaum, C. (1998) · Cited by 727
SemEval-2007 task 14: affective text
Strapparava, C., & Mihalcea, R. (2007) · Proceedings of the 4th International Workshop on Semantic Evaluations - SemEval '07 · doi:10.3115/1621474.1621487 · Cited by 602
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Cited by
Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications
Calvo, R. A., & D'Mello, S. (2010) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2010.1 · Cited by 1,893
Sentiment strength detection in short informal text
Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., & Kappas, A. (2010) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21416 · Cited by 1,449
Sentiment strength detection for the social web
Thelwall, M., Buckley, K., & Paltoglou, G. (2012) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21662 · Cited by 1,062
Current State of Text Sentiment Analysis from Opinion to Emotion Mining
Yadollahi, A., Shahraki, A. G., & Zaiane, O. R. (2018) · ACM Computing Surveys · doi:10.1145/3057270 · Cited by 489
Text Understanding from Scratch
Zhang, X., & LeCun, Y. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1502.01710 · Cited by 395
Metadata
- Authors
- Strapparava, C., & Mihalcea, R.
- Venue
- Proceedings of the 2008 ACM symposium on Applied computing
- Publisher
- ACM
- Published
- 2008-03-16
- Pages
- 1556-1560
- OpenAlex
- W2079521622
- Cited by
- 666
- References
- 19
- FWCI
- 15.63
- Type
- conference paper
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
