The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Semantic Sentiment Analysis of Twitter
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Citations
Cites
Twitter as a Corpus for Sentiment Analysis and Opinion Mining
Pak, A., & Paroubek, P. (2010) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/47akcj8foo4d · Cited by 2,704
Sentiment Analysis of Twitter Data
Agarwal, A., Xie, B., Vovsha, I., Rambow, O., & Passonneau, R. J. (2011) · Cited by 1,565
Twitter Sentiment Analysis: The Good the Bad and the OMG!
Kouloumpis, E., Wilson, T., & Moore, J. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v5i1.14185 · Cited by 1,225
Joint sentiment/topic model for sentiment analysis
Lin, C., & He, Y. (2009) · Proceedings of the 18th ACM conference on Information and knowledge management · doi:10.1145/1645953.1646003 · Cited by 961
Self-citationRobust Sentiment Detection on Twitter from Biased and Noisy Data
Barbosa, L., & Feng, J. (2010) · Cited by 883
Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments
Gimpel, K., Schneider, N., O'Connor, B., Das, D., Mills, D. P., Eisenstein, J., Heilman, M., Yogatama, D., Flanigan, J., & Smith, N. A. (2018) · Figshare · doi:10.1184/r1/6473609.v1 · Cited by 800
Sentiment Knowledge Discovery in Twitter Streaming Data
Bifet, A., & Frank, E. (2010) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-16184-1_1 · Cited by 573
Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments
Gimpel, K., Schneider, N., O'Connor, B., Das, D., Mills, D., Eisenstein, J., Heilman, M., Yogatama, D., Flanigan, J., & Smith, N. A. (2010) · doi:10.21236/ada547371 · Cited by 491
Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees
Moschitti, A. (2006) · Lecture Notes in Computer Science · doi:10.1007/11871842_32 · Cited by 452
User-level sentiment analysis incorporating social networks
Tan, C., Lee, L., Tang, J., Jiang, L., Zhou, M., & Li, P. (2011) · Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/2020408.2020614 · Cited by 419
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
Tweet sentiment analysis with classifier ensembles
da Silva, N. F. F., Hruschka, E. R., & Hruschka, E. R. (2014) · Decision Support Systems · doi:10.1016/j.dss.2014.07.003 · Cited by 431
Contextual semantics for sentiment analysis of Twitter
Saif, H., He, Y., Fernandez, M., & Alani, H. (2016) · Information Processing & Management · doi:10.1016/j.ipm.2015.01.005 · Cited by 425
Self-citationBig Data: Deep Learning for financial sentiment analysis
Sohangir, S., Wang, D., Pomeranets, A., & Khoshgoftaar, T. M. (2018) · Journal of Big Data · doi:10.1186/s40537-017-0111-6 · Cited by 390
A Study on Sentiment Analysis Techniques of Twitter Data
Alsaeedi, A., & Zubair, M. (2019) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2019.0100248 · Cited by 282
Metadata
- Authors
- Saif, H., He, Y., & Alani, H.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2012
- Pages
- 508-524
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1839863673
- Cited by
- 521
- References
- 17
- FWCI
- 29.79
- Type
- conference paper
- Language
- en
- Open access
- bronze
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- Saif, H., He, Y., & Alani, H. (2012). Semantic Sentiment Analysis of Twitter. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-642-35176-1_32
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
