The Method of Chinese Opinion Sentence Extraction and Polarity Identification Based on Sentimental Elements

Abstract

In this paper, we propose a new method for the opinion sentence extraction and its polarity identification in sentences which contain sentimental elements. In this method, the single sentimental element and Composite Sentimental Element are calculated respectively by sentimental dictionary and sentiment-based training corpus. After that, we design a model which is to extract objective & subjective sentences and analyze the polarity of the latter. This model can be used to extract the sentimental information in the two parties of sentimental elements. Finally, we applied this model in micro-blog sentences analyzing and proved its effectiveness.

Discriminating Topical Influencers Based on the User Relative Emotion

“…The study found that the use of sentimental words to classify emotional tendency is hard to fulfill the needs of the relative emotion discrimination task. Therefore, scholars have proposed the task of sentimental element extraction [34], [35]. The emotional element extraction task is also called fine-grained opinion mining, and most of its related work is to do sequence labeling.…”

Chinese Microblogs Sentiment Classification using Maximum Entropy

“…Since the enormous amount of users and its great effect, people find it necessary to take an insight look at this new form of message. Researches on microblogs fall into multiple areas, such as extraction of messages (Liu et al, 2012), extraction of opinion sentence (Ding, Liu, 2008;Liu et al, 2013), and determination of sentiment orientation (Ding, Liu, 2008;Go et al, 2009;Zhang et al, 2014). Generally speaking, researchers want to find out what people think through what they post on Weibo platform.…”