Big smog meets web science: Smog disaster analysis based on social media and device data on the web

Jiaoyan Chen, Huajun Chen*, Guozhou Zheng, Jeff Z. Pan, Honghan Wu, Ningyu Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Citations (Scopus)

Abstract

Nowadays, people are increasingly concerned about smog disaster and the caused health hazard. However, the current methods for big smog analysis are usually based on the traditional lagging data sources or merely adopt physical environment observations, which limit the methods' accuracy and usability. The discipline of Web Science, the research fields of which include web of people and web of devices, provides real time web data as well as novel web data analysis approaches. In this paper, both social web data and device web data are proposed for smog disaster analysis. Firstly, we utilize social web data to define and calculate Individual Public Health Indexes (IPHIs) for smog caused health hazard quantification. Secondly, we integrate social web data and device web data to build standard health hazard rating reference and train smog-health models for health hazard prediction. Finally, we apply the rating reference and models to online and location-sensitive smog disaster monitoring, which can better guide people's behaviour and government's strategy design for disaster mitigation.

Original languageEnglish
Title of host publicationWWW 2014 Companion
Subtitle of host publication Proceedings of the 23rd International Conference on World Wide Web
PublisherAssociation for Computing Machinery, Inc
Pages505-510
Number of pages6
ISBN (Electronic)9781450327459
DOIs
Publication statusPublished - 7 Apr 2014
Event23rd International Conference on World Wide Web, WWW 2014 - Seoul, Korea, Republic of
Duration: 7 Apr 201411 Apr 2014

Conference

Conference23rd International Conference on World Wide Web, WWW 2014
CountryKorea, Republic of
CitySeoul
Period7/04/1411/04/14

Fingerprint

Health hazards
Disasters
Personnel rating
Public health
Health
Monitoring

Keywords

  • Big smog
  • Device data
  • Health hazard
  • Social media
  • Stream data
  • Web science

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

Cite this

Chen, J., Chen, H., Zheng, G., Pan, J. Z., Wu, H., & Zhang, N. (2014). Big smog meets web science: Smog disaster analysis based on social media and device data on the web. In WWW 2014 Companion: Proceedings of the 23rd International Conference on World Wide Web (pp. 505-510). Association for Computing Machinery, Inc. https://doi.org/10.1145/2567948.2576941

Big smog meets web science : Smog disaster analysis based on social media and device data on the web. / Chen, Jiaoyan; Chen, Huajun; Zheng, Guozhou; Pan, Jeff Z.; Wu, Honghan; Zhang, Ningyu.

WWW 2014 Companion: Proceedings of the 23rd International Conference on World Wide Web. Association for Computing Machinery, Inc, 2014. p. 505-510.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chen, J, Chen, H, Zheng, G, Pan, JZ, Wu, H & Zhang, N 2014, Big smog meets web science: Smog disaster analysis based on social media and device data on the web. in WWW 2014 Companion: Proceedings of the 23rd International Conference on World Wide Web. Association for Computing Machinery, Inc, pp. 505-510, 23rd International Conference on World Wide Web, WWW 2014, Seoul, Korea, Republic of, 7/04/14. https://doi.org/10.1145/2567948.2576941
Chen J, Chen H, Zheng G, Pan JZ, Wu H, Zhang N. Big smog meets web science: Smog disaster analysis based on social media and device data on the web. In WWW 2014 Companion: Proceedings of the 23rd International Conference on World Wide Web. Association for Computing Machinery, Inc. 2014. p. 505-510 https://doi.org/10.1145/2567948.2576941
Chen, Jiaoyan ; Chen, Huajun ; Zheng, Guozhou ; Pan, Jeff Z. ; Wu, Honghan ; Zhang, Ningyu. / Big smog meets web science : Smog disaster analysis based on social media and device data on the web. WWW 2014 Companion: Proceedings of the 23rd International Conference on World Wide Web. Association for Computing Machinery, Inc, 2014. pp. 505-510
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