Abstract
Medical sentiment analysis can be considered as a two-step process comprising topic detection or health mention classification and the actual sentiment analysis. Health mention classification can be realised using topic detection methods such as topic modelling or named entity extraction. To be able to analyse expressed sentiments and their polarities, the text has to be pre-processed and relevant features have to be identified for classification. In this chapter, the different pre-processing tasks will be outlined and example methods to realise them will be presented. These include methods for text normalisation, feature extraction and feature selection.
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Denecke, K. (2023). Document Pre-processing. In: Sentiment Analysis in the Medical Domain. Springer, Cham. https://doi.org/10.1007/978-3-031-30187-2_9
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DOI: https://doi.org/10.1007/978-3-031-30187-2_9
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