Abstract
Every day a large amount of subjective information is generated through social networks such as Facebook® and Twitter®. The subjective information implies the opinions, beliefs, feelings and attitudes that people express towards different topics of interest. Moreover, this type of information is of great importance for companies, organizations or individuals, because it allows them to carry out actions that benefit them. Besides, sentiment analysis is the field that studies subjective information through natural language processing, computational linguistics, information retrieval and data mining techniques. Sentiment analysis is very useful in various domains, such as politics, marketing, tourism, among others. Actually, healthcare domain implies a large area of opportunity to obtain benefits using sentiment analysis, such as obtaining information about the patients’ mood, diseases, adverse drug reactions, epidemics, among others. However, healthcare domain has been very little explored. Therefore, in this chapter we propose a module based on sentiment analysis to obtain sentiments and emotions at the comment and entity levels from texts related to the healthcare domain. Also, different case studies are presented to validate the proposed module.
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Acknowledgements
The authors are grateful to the National Technological Institute of Mexico for supporting this work. This research paper was also supported by the Mexico’s National Council of Science and Technology (CONACYT), as well as by the Secretariat of Public Education (SEP) through the PRODEP program.
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Ramírez-Tinoco, F.J., Alor-Hernández, G., Sánchez-Cervantes, J.L., Salas-Zárate, M.d., Valencia-García, R. (2019). Use of Sentiment Analysis Techniques in Healthcare Domain. In: Alor-Hernández, G., Sánchez-Cervantes, J., Rodríguez-González, A., Valencia-García, R. (eds) Current Trends in Semantic Web Technologies: Theory and Practice. Studies in Computational Intelligence, vol 815. Springer, Cham. https://doi.org/10.1007/978-3-030-06149-4_8
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