Sentiment analysis in Facebook and its application to e-learning
作者：
Highlights：
• We describe a new method to support sentiment analysis in Facebook.
• We have implemented it in SentBuk, a Facebook application.
• We report results when using lexicon-based, machine-learning and hybrid approaches.
• The best accuracy was reached through the hybrid approach (83.27%).
• We propose several applications of this approach for e-learning.
摘要
•We describe a new method to support sentiment analysis in Facebook.•We have implemented it in SentBuk, a Facebook application.•We report results when using lexicon-based, machine-learning and hybrid approaches.•The best accuracy was reached through the hybrid approach (83.27%).•We propose several applications of this approach for e-learning.
论文关键词：Sentiment analysis,Social networks,User modeling,Adaptive e-learning
论文评审过程：Available online 7 August 2013.
论文官网地址：https://doi.org/10.1016/j.chb.2013.05.024
