Modeling Online Collective Emotions Through Knowledge Transfer

doi:10.1109/ISI.2017.8004909

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 互联网大数据与信息安全

	Modeling Online Collective Emotions Through Knowledge Transfer
	Saike He1 ; Xiaolong Zheng1 ; Daniel Zeng1,2
	2017-08-18
会议名称	IEEE Intelligence and Security Informatics 2017 Conference (ISI 2017)
会议录名称	Intelligence and Security Informatics (ISI), 2017 IEEE International Conference on
会议日期	22-24 July 2017
会议地点	Beijing, China
摘要	Online emotion diffusion is a compound process that involves interactions with multiple modalities. For instance, different behaviors influence the velocity and scale of emotion diffusion in online communities. Depicting and predicting massive online emotions helps to guide the trend of emotion evolution, thus avoiding unprecedented damages in crises. However, most existing work tries to depict and predict online emotions based on models not considering related modalities. There still lacks an efficient modeling framework that promotes performance by leveraging multi-modality knowledge, and quantifies the interactions among different modalities. In this paper, we elaborate a computational model to jointly depict online emotions and behaviors. By introducing a common structure, we can quantify how user emotions interact with the corresponding behaviors. To scale up to large dataset, we propose a hierarchical optimization algorithm to accelerate the convergence of the model. Evaluation on Sina Weibo dataset suggests that prediction error rate is lowered by 69 percent with the proposed model. In addition, the proposed model helps to explain how user emotions influence consequent behaviors in extreme situations.
关键词	Online Emotions Knowledge Transfer Social Crises
DOI	10.1109/ISI.2017.8004909
引用统计
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/15356
专题	多模态人工智能系统全国重点实验室_互联网大数据与信息安全
通讯作者	Xiaolong Zheng
作者单位	1.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 2.University of Chinese Academy of Sciences, Beijing, China
推荐引用方式 GB/T 7714	Saike He,Xiaolong Zheng,Daniel Zeng. Modeling Online Collective Emotions Through Knowledge Transfer[C],2017.

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