1 Institute of Psychology , Chinese Academy of Sciences, Beijing, China .
2 Department of Psychology, University of Chinese Academy of Sciences , Beijing, China .
Cyberpsychol Behav Soc Netw. 2017 Sep;20(9):533-539. doi: 10.1089/cyber.2017.0142. Epub 2017 Sep 6.
Growing interest in social events on social media came along with the rapid development of the Internet. Social events that occur in the "real" world can spread on social media (e.g., Sina Weibo) rapidly, which may trigger severe consequences and thus require the government's timely attention and responses. This article proposes to predict the trends of social events on Sina Weibo, which is currently the most popular social media in China. Based on the theories of social psychology and communication sciences, we extract an unprecedented amount of comprehensive and effective features that relate to the trends of social events on Chinese social media, and we construct the trends of prediction models by using three classical regression algorithms. We found that lasso regression performed better with the precision 0.78 and the recall 0.88. The results of our experiments demonstrated the effectiveness of our proposed approach.
社交媒体上社交活动的日益兴起伴随着互联网的飞速发展。现实世界中发生的社交事件可以在社交媒体(如新浪微博)上迅速传播,这可能引发严重后果,因此需要政府及时关注和应对。本文提出了预测新浪微博上社交事件趋势的方法,目前新浪微博是中国最受欢迎的社交媒体。基于社会心理学和传播学的理论,我们提取了前所未有的大量与中国社交媒体上社交事件趋势相关的全面而有效的特征,并使用三种经典回归算法构建了趋势预测模型。我们发现,套索回归的精度为 0.78,召回率为 0.88,表现更好。我们的实验结果证明了所提出方法的有效性。