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An alternative to that would be detecting language in texts automatically, then train a custom model for the language of your choice (if texts are not written in English), and finally, perform the analysis.
Usually, a lot of preprocessing is needed and that preprocessing makes use of a number of resources. sentiment lexicons), but many others have to be created (e.g. The use of the resources available requires a lot of coding experience and can take long to implement.However, machines can have some problems to identify those.Sometimes, the intended action can be inferred from the text, but sometimes, inferring it requires some contextual knowledge.This data can be very useful for commercial applications like marketing analysis, public relations, product reviews, net promoter scoring, product feedback, and customer service.Before going into further details, let's first give a definition of expressions that describe people’s sentiments, appraisals, and feelings toward a subject or topic.Sentiment analysis, just as many other NLP problems, can be modeled as a classification problem where two sub-problems must be resolved: In an opinion, the entity the text talks about can be an object, its components, its aspects, its attributes, or its features.It could also be a product, a service, an individual, an organization, an event, or a topic.This guide is divided into four sections: is a field within Natural Language Processing (NLP) that builds systems that try to identify and extract opinions within text.Usually, besides identifying the opinion, these systems extract attributes of the expression e.g.: Currently, sentiment analysis is a topic of great interest and development since it has many practical applications.This could be, for example, mapped onto a 5-star rating in a review, e.g.: Very Positive = 5 stars and Very Negative = 1 star.Some systems also provide different flavors of polarity by identifying if the positive or negative sentiment is associated with a particular feeling, such as, anger, sadness, or worries (i.e.