Abstract
Sentiment analysis has been applied to the datasets collected from social networking websites to get valuable insights. The exemplary growth of social networking has attracted researchers, and there has been a vast contribution in this area. In this chapter, we discuss the basics of sentiment analysis and its methodology, including data collection, data pre-processing, and feature extraction methods. Next, we discuss enhancement techniques for sentiment analysis, including text categorization, feature selection, data integration, ontology-based approaches, and so on. The chapter further provides information about available sentiment analysis tools, challenges, and evaluation metrics. We also discuss sentiment analysis applications and insights for further attention.
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Saxena, A., Reddy, H., Saxena, P. (2022). Introduction to Sentiment Analysis Covering Basics, Tools, Evaluation Metrics, Challenges, and Applications. In: Biswas, A., Patgiri, R., Biswas, B. (eds) Principles of Social Networking. Smart Innovation, Systems and Technologies, vol 246. Springer, Singapore. https://doi.org/10.1007/978-981-16-3398-0_12
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