| 融合多模态特征的社会多媒体谣言检测技术研究 |
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| 引用本文： | 金志威,曹娟,王博,王蕊,张勇东.融合多模态特征的社会多媒体谣言检测技术研究[J].南京气象学院学报,2017,9(6):583-592. |
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| 作者姓名： | 金志威 曹娟 王博 王蕊 张勇东 |
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| 作者单位： | 中国科学院计算技术研究所 智能信息处理实验室, 北京, 100190;中国科学院大学, 北京, 100049,中国科学院计算技术研究所 智能信息处理实验室, 北京, 100190;中国科学院大学, 北京, 100049,中国电子科技集团公司电子科学研究院创新中心, 北京, 100041,中国电子科技集团公司电子科学研究院创新中心, 北京, 100041,中国科学院计算技术研究所 智能信息处理实验室, 北京, 100190;中国科学院大学, 北京, 100049 |
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| 基金项目： | 国家自然科学基金（61525206）；中国电科创新基金（16105501）；中国电科联合基金（20166141B08020101） |
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| 摘 要： | 以微博为代表的社会媒体的蓬勃发展在加速信息交流的同时，也促使虚假谣言信息迅速在社会网络上传播，造成严重的后果.自动谣言检测问题受到了国内外学术界、产业界的广泛关注.围绕社会多媒体谣言检测这一问题，本文总结了融合多模态特征的谣言检测相关技术.首先从基本概念出发，阐述了谣言的定义和社会多媒体的特点，给出了社会多媒体谣言检测问题的定义.针对谣言检测面临的多模态特征抽取和模型构建两大难点，分别总结和归纳了各种类型的特征及其提取方法和不同的机器学习检测模型.这些特征和算法是检测谣言的基本手段，也是接下来研究的基础，可为进一步谣言检测的研究提供参考.
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| 关 键 词： | 谣言检测 社会媒体计算 多媒体计算 深度学习 多模态特征融合 新闻认证 |
| 收稿时间： | 2017/8/28 0:00:00 |
Rumor detection on social media with multimodal feature fusion |
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| JIN Zhiwei,CAO Juan,WANG Bo,WANG Rui and ZHANG Yongdong.Rumor detection on social media with multimodal feature fusion[J].Journal of Nanjing Institute of Meteorology,2017,9(6):583-592. |
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| Authors: | JIN Zhiwei CAO Juan WANG Bo WANG Rui and ZHANG Yongdong |
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| Institution: | Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, CAS, Beijing 100190;University of Chinese Academy of Sciences, Beijing 100049,Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, CAS, Beijing 100190;University of Chinese Academy of Sciences, Beijing 100049,Innovation Center, China Academy of Electronics and Information Technology, Beijing 100041,Innovation Center, China Academy of Electronics and Information Technology, Beijing 100041 and Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, CAS, Beijing 100190;University of Chinese Academy of Sciences, Beijing 100049 |
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| Abstract: | Social media,such as microblogs,has developed rapidly nowadays,which accelerates the information diffusion on the Internet.However,numerous false rumors fostered on social media are spreading widely on the social network and can result in serious consequences.It has become a huge concern in research and industry areas to detect rumors automatically on social media.Focused on the rumor detection task,this paper summarizes the approaches of multimodal fusion on this problem.Starting from the basic concepts,we give formal definitions of rumors and introduce the characteristics of social media.We summarize the studies on rumor detection into two major parts,i.e.,extracting effective multimodal features to identify rumors and constructing robust models to detect rumors.For each of the research aspects,we give detailed introduction based on existing studies.This paper can be served as a basic guidance to build state-of-the-art rumor detection models and a reference for future researches. |
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| Keywords: | rumor detection social media computing multimedia computing deep learning multimodal feature fusion news verification |
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