Evaluating Online Public Sentiments towards China: A Case Study of English and Chinese Twitter Discourse during the 2019 Chinese National Day

TL;DR

This study analyzes online sentiments towards China during the 2019 National Day using Twitter data, employing a hybrid sentiment analysis method with high accuracy, revealing sentiment patterns aligned with national relations and linguistic features.

Contribution

It introduces a hybrid SVM-dictionary approach for sentiment analysis of large-scale social media data, achieving over 96% accuracy and providing insights into cross-lingual and cross-national sentiment differences.

Findings

Sentiments in English and Chinese tweets tend to differ.

Tweet sentiments generally reflect official relations with China.

Linguistic features reveal different concerns among users.

Abstract

As the Internet gradually penetrates into people's daily lives and empowers everyone to demonstrate and exchange opinions and sentiments online, individual citizens are increasingly participating in the agenda-setting of public affairs and the design and implementation of official policies. The current study describes an approach to analyze online public sentiments using social media data and provides an example of Twitter discourse during the 2019 Chinese National Day. Over 300,000 tweets were collected between Sept 30 and Oct 3, and a hybrid method of SVM and dictionary was applied to evaluate the sentiments of the collected tweets. This method avoids complex structures while yielding an average accuracy of over 96% in most classifiers used in the study. The results indicate alignment between the time of National Day celebration activities and the expressed sentiments revealed in both English and Chinese tweets, although the sentiments of the two languages tend to be in different directions. The sentiment of tweets also diverges from nation to nation, but is generally consistent with the country's official relations with China to varying degrees. The linguistic features of the tweets suggest different concerns for Twitter users who have different sentiments towards China. At last, possible directions for further studies are indicated.