Civil aviation security public opinion emotion analysis method

Abstract

The present invention relates to a civil aviation public opinion emotion analysis method. The method comprises the steps of performing searching, preprocessing and word segmentation on microblog texts comprising keywords about civil aviation security public opinions in the internet; building a dictionary; grading each microblog text to obtain a microblog text emotion value; performing objective and subjective judgment on the microblog text according to the emotion value, so as to obtain a threat value of the microblog text for civil aviation security; and determining the threat level of the opinion in the microblog text for civil aviation security according to the threat value. The emotion value of the microblog text is determined by combining text semantics and microblog emoticons, the limitation of the dictionary and semantics rules are overcome, and the emotion value is determined more accurately. Due to full use of the characteristic of the microblog text, the threat level is determined more reasonably. The method differs from a machine learning method and is not trained with a large scale of tagged data, thereby being more suitable for processing of real-time data flow.

Description

technical field [0001] The invention belongs to the technical field of text sentiment analysis in natural language processing, and in particular relates to a method for sentiment analysis of civil aviation security public opinion. Background technique [0002] In the Internet age with rapid information expansion, more and more users tend to share their opinions or experiences through the Internet, so there are a large number of short texts with subjective emotions in social networks. Sina Weibo is an information sharing and communication platform that provides entertainment, leisure and life services for the public. At present, the number of active users of Sina Weibo remains at about 200 million. It inherits the advantages of traditional forums and blogs, combined with mobile terminals such as mobile phones, Enable information to be released and acquired quickly in real time. Weibo integrates entertainment, social networking, and marketing. It has gradually evolved from me...

AI Technical Summary

Problems solved by technology

However, these two methods mainly have the following problems in the application of microblog sentiment analysis: ① The method based on semantic understanding uses the method of constructing a benchmark lexicon and defining expression rules to perform pattern matching on the corpus. There are great limitations in blog text processing

②Machine learning-based methods are limited by the selection of features and the size of the corpus, and are prone to over-fitting effects, so they are not suitable for real-time bulk text processing

Images