Public Perception of Haze Weather Based on Weibo Comments
Abstract
:1. Introduction
2. Materials and Methods
- (1)
- Model construction: An analytical model on the trend of public perception of haze was constructed based on social perception calculation;
- (2)
- Data acquisition: We used “haze” and “PM2.5” as keywords and utilized crawlers to obtain microblog text data published by Weibo users from 1 January 2018 to 31 December 2018;
- (3)
- Data preprocessing: After the web crawlers obtained the microblog text resource information, the data was further cleaned by deduplication, removal of advertisement information, and processing of redundant information;
- (4)
- Keyword extraction: Natural language processing was used to extract perceptive keywords and semantic co-occurrence perception keywords from the pre-processed text data;
- (5)
- Data visualization: The extracted perceptual keywords and semantic co-occurrence perception keywords were visualized to generate a corresponding perceptual keyword co-occurrence matrix, s perceptual keyword cloud map, and a perceptual semantic network map;
- (6)
- Semantic analysis: The perceptive semantic network graph obtained through data visualization was analyzed using complex network topology characteristics;
- (7)
- Social perception analysis: Through the data mining analysis of the text information, the trend of the public’s perception of haze was further explored.
3. Results
3.1. Data Source
3.2. Data Analysis
3.2.1. Perceptual Keyword Analysis
3.2.2. Perceptual Co-occurrence Network Analysis
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Yang, Y.; Suh, S. Environmental Impacts of Products in China. Environ. Sci. Technol. 2011, 45, 4102–4109. [Google Scholar] [CrossRef] [PubMed]
- Xu, L.; Yang, G. Environmental Psychology: Environmental Perception and Behavior; Tongji University Press: Shanghai, China, 2002. [Google Scholar]
- Sheng, C.; Zhu, Y.; Liu, T. Public opinion analysis based on Weibo social network. Intell. Comput. Appl. 2019, 9, 57–59, 64. [Google Scholar]
- Pentland, A. Socially Aware Computation and Communication. Computer 2005, 38, 33–40. [Google Scholar] [CrossRef]
- Farrahi, K.; Gatica-Perez, D. What did you do today? Discovering daily routines from large-scale mobile data. In Proceedings of the 16th International Conference on Multimedia (ACM Mulitmedia), Vancouver, BC, Canada, 26–31 October 2008; pp. 849–852. [Google Scholar]
- Wang, Z. Event Extraction and Sentiment Analysis on Mricoblog; Shanghai Jiao Tong University: Shanghai, China, 2013. [Google Scholar]
- Conversi, D. Irresponsible Radicalisation: Diasporas, Globalisation and Long-Distance Nationalism in the Digital Age. J. Ethn. Migr. Stud. 2012, 38, 1357–1379. [Google Scholar] [CrossRef]
- Yi, S.; Li, J.; Li, X. Relationship between air quality and residents’ emotion—A case of Xi’an and Shanghai. J. Arid Land Resour. Environ. 2017, 31, 39–44. [Google Scholar]
- Huang, B. Research of Mining on the Public Opinion Information Based on Social Network; Harbin Institute of Technology: Harbin, China, 2017. [Google Scholar]
- Kay, S.; Zhao, B.; Sui, D. Can Social Media Clear the Air? A Case Study of the Air Pollution Problem in Chinese Cities. Prof. Geogr. 2015, 67, 351–363. [Google Scholar] [CrossRef]
- Fan, B.; Yang, W.; SUN, X. Public Emotion and Risk Perception Under the Influence of Haze—Based on a Survey of Microblog Users in Tianjin. J. Northeast. Univ. Soc. Sci. 2017, 19, 489–496. [Google Scholar]
- Yu, Z.-W.; Yu, Z.-Y.; Zhou, X.-S. Socially Aware Computing. Chin. J. Comput. 2012, 35, 16–26. [Google Scholar] [CrossRef]
- He, Y.; Li, J.; Li, S.; Ye, L. Research of Mining Important Online Reviews Based on Complex Network and Fusion Products Subject. Appl. Res. Comput. 2015, 32, 3569–3573. [Google Scholar]
- He, Y.; Li, J.; Ma, Y.; Li, S. Construction of Mining Model of Subject-oriented Online Reviews Based on Complex Network. Soft Sci. 2015, 29, 115–119. [Google Scholar]
- Li, X.; Xie, Q.; Hong, Z.; Huang, L. Study the Development Trends of Emerging Technologies Based on Socially Aware Analysis: A Case of Perovskite Solar Cells Technology. Sci. Technol. Prog. Policy 2018, 35, 15–24. [Google Scholar]
- Liu, J. Overall Network Analysis Handout—UCINET Practical Guide; Shanghai Century Publishing Group: Shanghai, China, 2009. [Google Scholar]
- Wang, L. Analysis of Air Quality Data Based on Complex Network Theory; Jiangsu University: Zhenjiang, China, 2017. [Google Scholar]
- Yao, Z.; Shang, K.; Xu, X. Fundamental Statistics of Weighted Networks. J. Univ. Shanghai Sci. Technol. 2012, 34, 18–26. [Google Scholar]
- Barrat, A.; Barthelemy, M.; Pastor-Satorras, R.; Vespignani, A. The architecture of complex weighted networks. Proc. Natl. Acad. Sci. USA 2004, 101, 3747–3752. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Season | Spring | Summer | Autumn | Winter |
---|---|---|---|---|
0.598 | 0.588 | 0.601 | 0.612 | |
1 | Causes 0.685 | Enjoy Life 0.692 | Treatment Method 0.715 | Health Hazard 0.727 |
2 | Ingredients 0.681 | Travel 0.678 | Take Measures 0.710 | Discomfort Symptoms 0.723 |
3 | Roots 0.674 | Happy Play 0.671 | Scientific Haze Prevention 0.709 | Pharyngitis 0.716 |
4 | Contaminant Composition Level 0.675 | Pleasant Roads 0.668 | Boycotts Haze Days 0.694 | Scorpion Pain 0.703 |
5 | Formation 0.663 | Wind And Sun 0.662 | Haze Prevention Measures 0.687 | Phlegm 0.695 |
6 | Structure 0.652 | Haze Disappears 0.647 | Keep Clean 0.675 | Cough 0.684 |
7 | Construct 0.648 | Hiking 0.639 | Mask 0.658 | Asthma Attack 0.661 |
8 | Source of Pollution 0.637 | Sunshine 0.634 | Filtered Air 0.631 | Chest Tightness 0.652 |
9 | Pollution Attribution 0.626 | Sunny 0.621 | Scientific Defense 0.618 | Ecological Crisis 0.647 |
10 | Air Pollution 0.619 | High Quality Air 0.607 | Protection 0.611 | Chronic Disease 0.634 |
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Zhang, Q.; Chen, J.; Liu, X. Public Perception of Haze Weather Based on Weibo Comments. Int. J. Environ. Res. Public Health 2019, 16, 4767. https://doi.org/10.3390/ijerph16234767
Zhang Q, Chen J, Liu X. Public Perception of Haze Weather Based on Weibo Comments. International Journal of Environmental Research and Public Health. 2019; 16(23):4767. https://doi.org/10.3390/ijerph16234767
Chicago/Turabian StyleZhang, Qiang, Jinshou Chen, and Xueyan Liu. 2019. "Public Perception of Haze Weather Based on Weibo Comments" International Journal of Environmental Research and Public Health 16, no. 23: 4767. https://doi.org/10.3390/ijerph16234767