Text annotation is adding extra details, labels, and definitions to texts. When different people read a specific text, they may experience a wide range of emotions and sentiments and have different opinions towards this text. In comparison with humans, machines can’t convey emotions from the text. To help artificial intelligence understand what people feel about a particular text, people need to annotate the text and indicate what exactly this information means.
Text annotation is used for natural language processing (NLP) solutions such as chatbots, automatic speech recognition, and sentiment analysis programs. Extensive datasets of annotated text are needed to train NLP systems.
What is Sentiment Annotation?
Sentiment annotation is the process of labeling people’s emotions, sentiments, and opinions toward a particular text. When emotional intelligence is subjective, it is difficult for artificial intelligence to decipher what people feel in specific texts. As a result, machines find it challenging to understand humor, sarcasm, and even informal ways of conversation.
Companies can use sentiment annotation to better understand the customers’ reviews of certain products. A robust sentiment analysis model will better decipher the emotional connotation of the customer and product reviews, polls, emails, and social media posts.
Sentiment Annotation for Brand Reputation
Sentiment annotation can be a valuable tool for growing a brand’s reputation. People can discuss certain brands and their products on social media posts, website reviews, online conversations, forum discussions, and news websites. Reading product reviews has become an essential step in the buying process. Before making a purchase, customers check at least ten reviews, and 57% only trust a company with a star rating of 4 or above. Sentiment analysis is a great way to monitor your brand’s reputation, determine what is good or bad about your company, and learn more about your customers.
Conclusion
Text annotation is an inevitable step for growing machine learning and artificial intelligence. To improve the machine’s emotional intelligence, people use sentiment annotation. Sentiment annotation is extremely useful for businesses as it can help them better understand the emotions and opinions of their customers and thus improve their service and grow their brand.
