Sentiment and emotion analysis about peruvian gastronomy using text mining with Python
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Abstract
The aim of the study was to show the process of applying sentiment analysis techniques, also known as opinion mining (OM), for the classification of feelings and emotions in opinion texts automatically. As a case study, the analysis of feelings and emotions in reviews, which come from TripAdvisor and Google, about Peruvian gastronomy is presented. To achieve the objective, the phases of information extraction (opinions), preprocessing and classification have been followed; This is complemented using available Python libraries, with special emphasis on those that allow analysis of texts in Spanish. As a result, the usefulness of a library available as free software with very good results for automating the review classification process is shown. On the other hand, it shows that opinions about Peruvian gastronomy are classified as positive with 68 % vs. 11 % of reviews classified as negative.
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