%0 Journal Article
%A HUANG Miao
%A HUANG Pei
%T Content Detection Based on Knowledge Relation: Cases of Health Rumors
%D 2020
%R 10.19722/j.cnki.1008-7729.2019.0369
%J Journal of Beijing University of Posts and Telecommunications(Social Sciences Edition)
%P 1-6
%V 22
%N 1
%X Ubiquitous informatization in the society enables the Internet to be the most efficient access for acquiring knowledge However, with the decrease of barriers for releasing and distributing information, frequent occurrence of rumors has become a social problem Moreover, health topics are closely related to individuals lives, so they are the worst-hit area of rumors Based on content analysis of rumors in WeChat and Toutiaocom, the research question of how to detect rumors through the characteristics of knowledge relation is proposed In order to explore and present the knowledge relation, a social networking analysis tool was adopted to visualize the cluster of high frequency words of weight-loss rumors that were refined from the rumor base at Bytedance With the analysis through visualization, it is found that the co-occurrence relation is better than the similarity relation at discovering common phrases and popular topics of knowledge-based rumors Lastly, in a normative perspective, a mechanism for detecting newborn rumors is constructed, which should integrate technologies of knowledge graph and labeling
%U https://journalsk.bupt.edu.cn/EN/10.19722/j.cnki.1008-7729.2019.0369