Sentiment analysis is a term from the fields of artificial intelligence, big data and smart data, as well as digital transformation. It describes a method with which computers can recognise sentiment in texts – in other words, finding out whether a tweet, product review or comment, for example, is meant to be positive, negative or neutral.
The basis of sentiment analysis lies in modern algorithms that sift through vast amounts of text and analyse its tone. Companies use this technique to gain a better understanding of what customers think about them, how products are received, or the impact of a marketing campaign.
Imagine you run an online shop and receive hundreds of reviews daily. With sentiment analysis, a system automatically detects whether your customers are satisfied or dissatisfied. For example, it might report that many complaints are piling up about a new phone case. This allows you to react quickly and improve your offering.
Sentiment analysis is therefore a useful tool for analysing large volumes of data and making informed decisions based on data, without having to carry out time-consuming individual analyses.
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