Please wait a minute...
Data Analysis and Knowledge Discovery  0, Vol. Issue (): 1-    DOI: 10.11925/infotech. 2096-3467.2019.1145
Current Issue | Archive | Adv Search |
CLOpin: A Cross-lingual Knowledge Graph Framework for Public Opinion Analysis and Early Warning
Liang Ye,Li Xiaoyuan,Xu Hang,Hu Yiran
(School of Information Science and Technology, Beijing Foreign Studies University, Beijing 100089, China)
(School of Asian Studies, Beijing Foreign Studies University, Beijing 100089, China)
Download:
Export: BibTeX | EndNote (RIS)      
Abstract  

[Objective] To explore the relation of information mapping among different languages, so as to achieve effective monitoring of public opinion outside the country and provide positive guidance to domestic audiences. [Method] A cross-linguistic knowledge mapping platform CLOpin is proposed in the field of public opinion analysis and early warning. The platform designs several toolsets for different scenarios to process cross-linguistic data sets, which can integrate data from various sources efficiently and construct a knowledge mapping to guide the implementation of cross-linguistic public opinion analysis and early warning. [Result] The results show that the information integrity of CLKG in one hour is 13.9% higher than single language knowledge graph, and only 5.2% lower than that of the latter in 24 hours. [Limitations] The construction of CLKG is constrained by the scarcity of domain experts, which has become the bottleneck of the construction of knowledge graph of non-common language. [Conclusion] In CLOpin platform, knowledge from different sources complements each other, which has a significant effect on expanding the amount of event information, and is conducive to accurately grasping the dynamics of public opinion and making early warning accordingly.

Key words Cross-lingual      knowledge graph      Public opinion analysis      Early warning      
Published: 23 April 2020
ZTFLH:  TP393,G250  

Cite this article:

Liang Ye, Li Xiaoyuan, Xu Hang, Hu Yiran. CLOpin: A Cross-lingual Knowledge Graph Framework for Public Opinion Analysis and Early Warning . Data Analysis and Knowledge Discovery, 0, (): 1-.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech. 2096-3467.2019.1145     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y0/V/I/1

[1] Liu Kan, Xu Qinya, Yu Lu. Constructing Knowledge Graph for Business Environment[J]. 数据分析与知识发现, 2022, 6(4): 82-96.
[2] Zhang Wei, Wang Hao, Chen Yuetong, Fan Tao, Deng Sanhong. Identifying Metaphors and Association of Chinese Idioms with Transfer Learning and Text Augmentation[J]. 数据分析与知识发现, 2022, 6(2/3): 167-183.
[3] Liu Zhenghao, Qian Yuxing, Yi Tianlong, Lv Huakui. Constructing Knowledge Graph for Financial Securities and Discovering Related Stocks with Knowledge Association[J]. 数据分析与知识发现, 2022, 6(2/3): 184-201.
[4] Cheng Zijia, Chen Chong. Question Comprehension and Answer Organization for Scientific Education of Epidemics[J]. 数据分析与知识发现, 2022, 6(2/3): 202-211.
[5] Hou Dang, Fu Xiangling, Gao Songfeng, Peng Lei, Wang Youjun, Song Meiqi. Mining Enterprise Associations with Knowledge Graph[J]. 数据分析与知识发现, 2022, 6(2/3): 212-221.
[6] Wu Jinhong, Mu Keliang. Automatic Identifying Abnormal Behaviors of International Journals[J]. 数据分析与知识发现, 2022, 6(2/3): 385-395.
[7] Zhou Yang,Li Xuejun,Wang Donglei,Chen Fang,Peng Lijuan. Visualizing Knowledge Graph for Explosive Formula Design[J]. 数据分析与知识发现, 2021, 5(9): 42-53.
[8] Shen Kejie, Huang Huanting, Hua Bolin. Constructing Knowledge Graph with Public Resumes[J]. 数据分析与知识发现, 2021, 5(7): 81-90.
[9] Ruan Xiaoyun,Liao Jianbin,Li Xiang,Yang Yang,Li Daifeng. Interpretable Recommendation of Reinforcement Learning Based on Talent Knowledge Graph Reasoning[J]. 数据分析与知识发现, 2021, 5(6): 36-50.
[10] Li He,Liu Jiayu,Li Shiyu,Wu Di,Jin Shuaiqi. Optimizing Automatic Question Answering System Based on Disease Knowledge Graph[J]. 数据分析与知识发现, 2021, 5(5): 115-126.
[11] Dai Bing,Hu Zhengyin. Review of Studies on Literature-Based Discovery[J]. 数据分析与知识发现, 2021, 5(4): 1-12.
[12] Zhu Dongliang, Wen Yi, Wan Zichen. Review of Recommendation Systems Based on Knowledge Graph[J]. 数据分析与知识发现, 2021, 5(12): 1-13.
[13] Yu Chuanming, Zhang Zhengang, Kong Lingge. Comparing Knowledge Graph Representation Models for Link Prediction[J]. 数据分析与知识发现, 2021, 5(11): 29-44.
[14] Chen Shiji, Qiu Junping, Yu Bo. Topic Analysis of LIS Big Data Research with Overlay Mapping[J]. 数据分析与知识发现, 2021, 5(10): 51-59.
[15] Shao Qi,Mu Dongmei,Wang Ping,Jin Chunyan. Identifying Subjects of Online Opinion from Public Health Emergencies[J]. 数据分析与知识发现, 2020, 4(9): 68-80.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn