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The Role of Text Pre-processing in Sentiment Analysis
Open accessAbstract
It is challenging to understand the latest trends and summarise the state or general opinions about products due to the big diversity and size of social media data, and this creates the need of automated and real time opinion extraction and mining. Mining online opinion is a form of sentiment analysis that is treated as a difficult text classification task. In this paper, we explore the role of text pre-processing in sentiment analysis, and report on experimental results that demonstrate that with appropriate feature selection and representation, sentiment analysis accuracies using support vector machines (SVM) in this area may be significantly improved. The level of accuracy achieved is shown to be comparable to the ones achieved in topic categorisation although sentiment analysis is considered to be a much harder problem in the literature.
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Cites
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Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
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Schölkopf, B., Platt, J. C., Shawe-Taylor, J., Smola, A. J., & Williamson, R. C. (2001) · Neural Computation · doi:10.1162/089976601750264965 · Cited by 6,168
Cited by
Naseem, U., Razzak, I., Khan, S. K., & Prasad, M. (2021) · ACM Transactions on Asian and Low-Resource Language Information Processing · doi:10.1145/3434237 · Cited by 194
Sentiment analysis: A survey on design framework, applications and future scopes
Bordoloi, M., & Biswas, S. K. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10442-2 · Cited by 183
A survey on aspect-based sentiment classification
Brauwers, G., & Frasincar, F. (2023) · ACM Computing Surveys · doi:10.1145/3503044 · Cited by 165
The application and comparison of web services for sentiment analysis in tourism
Gao, S., Hao, J., & Fu, Y. (2015) · 2015 12th International Conference on Service Systems and Service Management (ICSSSM) · doi:10.1109/icsssm.2015.7170341 · Cited by 41
Metadata
- Authors
- Haddi, E., Liu, X., & Shi, Y.
- Venue
- Procedia Computer Science
- Publisher
- Elsevier BV
- Published
- 2013
- Volume
- 17
- Pages
- 26-32
- ISSN
- 1877-0509 (ISSN-L)
- OpenAlex
- W2156741031
- Cited by
- 619
- References
- 2
- FWCI
- 14.31
- Type
- conference paper
- Language
- en
- Open access
- diamond
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