Real-time Opinion Extraction and Classification for Vietnamese Posts on Social Networks
Thuong‐Cang Phan, Anh-Cang Phan, Thanh-Ngoan Trieu · 2020
The growth of social networks changes the way people communicate and interact with each other. People have a tendency to give their thoughts and feelings on social networks. Thus, opinion mining posts on social networks is meaningful for companies and governments in terms of business and management. In this research, we propose a new approach for real-time extraction and classification for Vietnamese posts on social networks. There is an integration of Apache Kafka and Spark Streaming for large scale data collecting and processing. We use statistical methods for opinion extraction and classification. Experiments were conducted on a Spark cluster with real-time data stream collected from Facebook.