关键词: 金融领域, 情感分析, 位置关系, 支持向量机（SVM）, 依存分析

Abstract: The linkages between users emotional tendencies and market fluctuations to monitor and handle the market price of exception play an important role, so the sentiment analysis of user-generated text in financial sector becomes meaningful. However, due to the longer sentences and term of the financial sector, and not many ready-made emotional corpus, sentiment analysis research in this field is still relatively small. Based on the characteristics of financial sector, it uses the SVM classification with Stanford syntactic dependency analysis to calculate the document emotional value which fully takes into account the characteristics of emotional words, the words position weights and the modification of relationship between each other. Through the experimentation online extraction data which from the important financial website, the integrated value of F reaches 82.1%, more accurate than other methods in the literature.

Key words: financial domain, sentiment analysis, positional relationship, Support Vector Machine（SVM）, dependency parsing