Method of classifying web text information sentiments

Abstract

The invention discloses a method of classifying web text information sentiments, comprising the following steps of 1, judging whether a document is news, if yes, just extracting a title for sentiment classification, and if not, carrying out sentiment classifying on the whole document; 2, preprocessing the document to be classified; 3, classifying the document according to text length: calculating a feature weight for a document longer than 140 characters by using TF-IDF (term frequency-inverse document frequency), and carrying out classification by using a trained logistic regression classifier; and carrying classification on a document longer than 140 characters by using manual sentiment classification rules. Compared with the prior art, the method has the advantages that a technical route combining a classifier and field expert formulated classification features is constructed by using machine learning algorithm according to different features of long and short texts, and it is possible to timely find related reactionary information, sensitive information and negative information in online public opinions.

Description

technical field [0001] The invention belongs to the field of natural language processing and relates to a method for emotional classification of network text information. Background technique [0002] As a new type of media, the Internet has played more and more roles in smoothing public opinion, expressing appeals, supervising public opinion, and participating in state affairs. More and more people use the Internet to express their appeals in interests, politics, etc. One's own attitudes or views on hot social issues such as people's livelihood, justice, and anti-corruption. Especially when mass or unexpected events occur, people often pass or obtain information through the Internet in the first place. But at the same time, some hostile forces take advantage of the hidden environment of the Internet to create online public opinion that deviates from the mainstream political culture, undermining political stability and social harmony; Netizens vent their emotions and publi...

AI Technical Summary

Problems solved by technology

But at the same time, some hostile forces take advantage of the hidden environment of the Internet to create online public opinion that deviates from the mainstream political culture, undermining political stability and social harmony; Netizens vent their emotions and publish vulgar and gray remarks on the Internet

However, traditional manual methods are difficult to deal with the collection and judgment of massive information on the Internet. Therefore, automated sentiment classification methods are needed to judge Internet public opinion information and realize the key discovery of reactionary, sensitive, negative and other public opinion information.

Images