  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.
