Text sentiment analysis is to understand the author’s emotions in a specific text. Sentiment analysis of text language refers to the combination of natural language processing, text mining, and technical computers in the fields of language to extract emotional information in text. Collaborative analysis and research by the DiVoMiner® team can automatically identify the emotions or tendencies expressed in the text (marked as positive, negative or neutral). The technology is applying for a patent.

Based on the team’s update of the algorithm model and the rich corpus, the accuracy of sentiment analysis of specific categories of materials has reached 0.7 to 0.9 (within industry acceptance). The test results are as follows. It is recommended that the user determine the applicability of the model according to the specific research situation.