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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 121))

Abstract

Opinion mining, generally referred to sentiment analysis, deals with the sentiments of people in terms of their opinions regarding any specific object, idea, topic or product. These opinions can be positive, negative or neutral. Opinion mining is gaining its importance in almost each and every domain such as product and services, financial services, health care or even politics. The task of opinion mining is divided into series of steps such as dataset acquisition, opinion identification, aspect extraction, classification, report summary and evaluation. Among these steps, aspect extraction is the most important one. This paper presents an overview of opinion mining and discusses aspect extraction methodologies proposed in the literature.

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Sonia (2020). Opinion Mining Techniques and Its Applications: A Review. In: Singh, P., Pawłowski, W., Tanwar, S., Kumar, N., Rodrigues, J., Obaidat, M. (eds) Proceedings of First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019). Lecture Notes in Networks and Systems, vol 121. Springer, Singapore. https://doi.org/10.1007/978-981-15-3369-3_41

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