Ontology-Driven Affective Chinese Text Analysis and Evaluation Method

Abstract

This paper studies text affective analysis from three different levels: words, sentences and discourses. Firstly, affective lexicon ontology is constructed by employing the manual and automatic classification methods referred to the present emotional classification. Then affective analysis of sentences and discourses is completed by emotional information of affective lexicon ontology. For sentential recognition, the lexical emotion information and semantic features are appended into Condition Random Fields, and the emotional chain of a text document is generated. Finally affective structure of a text document is evaluated by two different methods as single sentence evaluation and joint sentence evaluation. In analyzing the discourses, affective tone is acquired through Emotional Largest Chain method and Support Vector Machine method.