Huawei Certified ICT Associate – Artificial Intelligence (HCIA-AI) Practice Exam

Sentiment analysis is a common application of text classification because it involves categorizing text data based on the sentiments or emotions expressed within that text. This process typically requires a model to analyze the words used and their context to determine whether the sentiment is positive, negative, or neutral. Text classification techniques are employed to automate this task, allowing businesses and researchers to analyze customer feedback, social media posts, and reviews on a large scale. By using machine learning algorithms and natural language processing, organizations can gain insights into public perception and improve their products or services based on the identified sentiments.

In contrast, image recognition pertains to the analysis of visual data, data encryption focuses on securing information through encoding, and network security involves protecting networks from unauthorized access and threats. These areas, while important in their own right, do not pertain to the classification of text, which is why sentiment analysis stands out as the correct application in this context.