TY  - CONF
ID  - SisLab2690
UR  - http://nafosted-nics.org
A1  - Nguyen, Xuan Duc
A1  - Nguyen, Minh Duc
A1  - Tran, Mai Vu
A1  - Phan, Xuan Hieu
A1  - Pham, Bao Son
Y1  - 2017/11/24/
N2  - The exponential growth of social media has created informative content, which leads to the emersion of social listening tools, in order to serve the need of companies and organizations. These tools are developed mainly in English language and for those which deal with Vietnamese, they lack the analysis capabilities to capture insightful information. In our research, we propose a framework to automatically extract and analyze information from social media, including online news and social networks. Our framework consists of multiple modules: data crawler, analysis module (topic analysis, sentiment analysis, event detection), visualization module. The results for analysis modules are promising: F1-score for topic analysis is 53%, average accuracy for sentiment analysis (using Maximum Entropy with three classes) is 62% and F1-score for event detection is 88.36%.
TI  - VNU-SMM: A social media monitoring framework on vietnamese online news
SP  - 269
M2  - Hanoi, Vietnam
AV  - none
EP  - 274
T2  - 2017 4th NAFOSTED Conference on Information and Computer Science (NICS 2017)
ER  -