Sentiment classification of Chinese Weibo based on extended sentiment dictionary and organisational structure of comments

Abstract

Sentiment classification can provide the decision support of social applications such as trend judgment, public opinion monitoring, etc. However, the accuracy of sentiment classification for Chinese Weibo is still not satisfactory due to the complexity of Chinese. In addition, affected by the different organisational structure levels, the sentiment tendency of fewer Weibo Comments may be judged to be the opposite. To solve the problem above, this paper presents a Chinese sentiment classification model based on extended sentiment dictionary and organisational structure of comments. First, the sentiment dictionary can be extended by using seven dictionaries, which include the base sentiment dictionary and six additional dictionaries. Then, the sets of rules are constructed, which include inter-sentence rules and organisational structure rules. Finally, comments on three hot topics are crawled and used to make the data sets for sentiment calculation. Accordingly, based on the result of sentiment calculation, sentiment classification is completed. The effectiveness of the proposed model is verified through comparison experiments, and the experimental results are also discussed.

KEYWORDS:

• Sentiment dictionary
• Weibo hot topics
• sentiment classification
• organisational structure

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research work was supported by the National Natural Science Foundation of China [grant number 62076006], and The University Synergy Innovation Program of Anhui Province [grant number GXXT-2021-008].