Abstract— Sentiment analysis and opinion mining are active research trends in data mining. The explosion of social media such as social networks has created unprecedented opportunities for data mining research community. Analyzers can study and analyze users’ opinions, attitudes, and emotions about news or social events. Our focus in this work is to propose a way to gauge tourist satisfaction based on some criteria set forth in the ranking of China's Feature Tourist City, by reviewing Natural Resources, Tourist Goods, and History and Culture of the city from the social network. The tweets collected from Sina Weibo in Macao have gone through a series of process to reach the expected data format and then be eventually analyzed. A dataset of 418,056 tweets from 2013 and 194,880 tweets from 2014 is analyzed in this work. Tourist satisfaction is calculated and the result indicates that the tourists’ overall satisfaction towards Macao is generally positive.
— Data mining, Macao, sentiment analysis, Sina Weibo.
Rita T. Tse is with the Computing Program, Macao Polytechnic Institute, Macao, China (e-mail: firstname.lastname@example.org).
Cite: Rita T. Tse, " Application of Data Mining in Sina Weibo — Sentiment Indicator to Gauge Tourist Satisfaction in Macao," International Journal of Innovation, Management and Technology vol. 7, no. 2, pp. 80-85, 2016.