The DOI matches its Crossref record; 238 of the 238 references it cites were found in a registry or an index.
A survey on opinion mining and sentiment analysis: Tasks, approaches and applications
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“Overall, sentiment analysis is considered as a machine learning task that analyzes texts for polarity, such as “positive”, “negative”, or “neutral” along with more intense emotions like very happy, happy, sad, very sad, angry, have interest, or not interested etc.”
From Machine learning: Algorithms, real-world applications and research directions (2021) · cites this paper as [90]
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Citations
Cites
A tutorial on hidden Markov models and selected applications in speech recognition
Rabiner, L. R. (1989) · Proceedings of the IEEE · doi:10.1109/5.18626 · Cited by 22,743
WordNet: a lexical database for English
Miller, G. A. (1995) · Communications of the ACM · doi:10.1145/219717.219748 · Cited by 14,015 · cited 4×
“WordNet-Affect [4], SentiWordNet [5, 6], WordNet [133], Opinion Lexicon (OL) [38], AFINN [55], SO-CAL [69], Subjectivity Lexicon [104], General Inquirer [105], SenticNet [106], SentiSense [113], and Micro-WNOp [119] together.”
BackgroundMethodInfluentialMining and summarizing customer reviews
Hu, M., & Liu, B. (2004) · Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/1014052.1014073 · Cited by 7,793
Toward principles for the design of ontologies used for knowledge sharing?
Gruber, T. R. (1995) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.1995.1081 · Cited by 7,753
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
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
Socher, R., Perelygin, A., Wu, J., Chuang, J., Manning, C. D., Ng, A., & Potts, C. (2013) · Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d13-1170 · Cited by 6,878
Opinion Mining and Sentiment Analysis
Pang, B., & Lee, L. (2008) · now publishers, Inc. eBooks · doi:10.1561/9781601981516 · Cited by 6,720
Opinion mining and sentiment analysis
Pang, B., & Lee, L. (2008) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000011 · Cited by 6,372
Twitter mood predicts the stock market
Bollen, J., Mao, H., & Zeng, X. (2011) · Journal of Computational Science · doi:10.1016/j.jocs.2010.12.007 · Cited by 5,206
Freebase: a collaboratively created graph database for structuring human knowledge
Bollacker, K., Evans, C., Paritosh, P., Sturge, T., & Taylor, J. (2008) · Proceedings of the 2008 ACM SIGMOD international conference on Management of data · doi:10.1145/1376616.1376746 · Cited by 4,852
Cited by
Machine learning: Algorithms, real-world applications and research directions
Sarker, I. H. (2021) · SN Computer Science · doi:10.1007/s42979-021-00592-x · Cited by 5,583
A survey on sentiment analysis methods, applications, and challenges
Wankhade, M., Rao, A. C. S., & Kulkarni, C. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10144-1 · Cited by 1,528
Sentiment analysis using deep learning architectures: a review
Yadav, A., & Vishwakarma, D. K. (2020) · Artificial Intelligence Review · doi:10.1007/s10462-019-09794-5 · Cited by 841
Sentiment 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
Decision support from financial disclosures with deep neural networks and transfer learning
Kraus, M., & Feuerriegel, S. (2017) · Decision Support Systems · doi:10.1016/j.dss.2017.10.001 · Cited by 312
Metadata
- Authors
- Ravi, K., & Ravi, V.
- Venue
- Knowledge-Based Systems
- Publisher
- Elsevier BV
- Published
- 2015-11
- Volume
- 89
- Pages
- 14-46
- ISSN
- 0950-7051 (ISSN-L)
- OpenAlex
- W2215376118
- Cited by
- 1,306
- References
- 238
- FWCI
- 105.73
- Type
- journal article
- Language
- en
- Open access
- closed
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- Ravi, K., & Ravi, V. (2015). A survey on opinion mining and sentiment analysis: Tasks, approaches and applications. Knowledge-Based Systems. https://doi.org/10.1016/j.knosys.2015.06.015
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
