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 \u2013 in other words, finding out whether a tweet, product review or comment, for example, is meant to be positive, negative or neutral.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>","protected":false},"excerpt":{"rendered":"