Evaluating Social Media Response to Urban Flood Disaster: Case Study on an East Asian City (Wuhan, China)
Abstract
:1. Introduction
2. The Flood Event in Wuhan City in the Summer of 2016
3. Data and Methods
3.1. Data Collection
3.2. Methods
4. Results
4.1. General Overview
4.2. Classification of Messages
4.3. Messages Posted by Organization and Individual Accounts
4.4. Pearson Correlation between Messages and Precipitation Amount
4.5. Dissemination Speed
4.6. Reposting Relations in Social Networks
5. Discussion
5.1. Responses to Disasters on Social Media in Western Countries and China
5.2. Differences in Responses to Various Natural Disasters
5.3. Emergency Management Models
5.4. Factors That Influence the Use of Social Media in Disasters
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Information Messages | Action Messages | Opinion Messages | Emotion Messages | Off-Topic Messages | |
---|---|---|---|---|---|
Number (Proportion to Total Number) | 11933 (70%) | 1875 (11%) | 1534 (9%) | 1364 (8%) | 341 (2%) |
Average Number of Reposts | 3.82 | 8.19 | 5.95 | 1.54 | 21.25 |
Average Number of Comments | 3.40 | 8.28 | 8.10 | 3.10 | 23.68 |
Average Number of Likes | 9.33 | 34.91 | 17.92 | 10.44 | 27.23 |
The Same Day N = 21 | One-Day Lag N = 20 | Two-Day Lag N = 19 | Three-Day Lag N = 18 | |
---|---|---|---|---|
NMP | 0.482 ** (P = 0.027) | 0.542 ** (P = 0.014) | 0.200 (P = 0.413) | 0.130 (P = 0.606) |
TNR | 0.487 ** (P = 0.025) | 0.411 * (P = 0.072) | 0.089 (P = 0.717) | 0.201 (P = 0.423) |
NMR | 0.502 ** (P = 0.020) | 0.545 ** (P = 0.013) | 0.122 (P = 0.617) | 0.084 (P = 0.739) |
NUA | 0.485 ** (P = 0.026) | 0.540 ** (P = 0.014) | 0.195 (P = 0.423) | 0.126 (P = 0.617) |
Information Messages | Action Messages | Opinion Messages | Emotion Messages | |
---|---|---|---|---|
NMP | 1 | 1 | 1 | 0 |
TNR | 0 | 1 | 3 | 1 |
NMR | 1 | 1 | 1 | / |
NUA | 1 | 1 | 1 | 0 |
Order | Account Name | Account Type | NMP | TNR | Fans (Million) |
---|---|---|---|---|---|
1 | People’s Daily | News organization | 5 | 4517 | 68.6 |
2 | CAIJING | News organization | 3 | 4183 | 28.73 |
3 | Small grain that wants to travel | Individual (celebrity) | 1 | 3991 | 0.79 |
4 | Engineer Charles Shef | Individual (celebrity) | 1 | 3040 | 0.07 |
5 | Global Times | News organization | 4 | 2014 | 14.07 |
6 | Chutian Metropolis Daily | News organization | 2 | 1882 | 11.12 |
7 | Surging News | News organization | 1 | 1796 | 11.1 |
8 | Headline News | News organization | 4 | 1602 | 54.82 |
9 | Sina News | News organization | 3 | 1241 | 13.58 |
10 | Wuhan Tongcheng Association | Social organization | 5 | 1105 | 0.95 |
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Cheng, X.; Han, G.; Zhao, Y.; Li, L. Evaluating Social Media Response to Urban Flood Disaster: Case Study on an East Asian City (Wuhan, China). Sustainability 2019, 11, 5330. https://doi.org/10.3390/su11195330
Cheng X, Han G, Zhao Y, Li L. Evaluating Social Media Response to Urban Flood Disaster: Case Study on an East Asian City (Wuhan, China). Sustainability. 2019; 11(19):5330. https://doi.org/10.3390/su11195330
Chicago/Turabian StyleCheng, Xiaoxue, Guifeng Han, Yifan Zhao, and Lin Li. 2019. "Evaluating Social Media Response to Urban Flood Disaster: Case Study on an East Asian City (Wuhan, China)" Sustainability 11, no. 19: 5330. https://doi.org/10.3390/su11195330
APA StyleCheng, X., Han, G., Zhao, Y., & Li, L. (2019). Evaluating Social Media Response to Urban Flood Disaster: Case Study on an East Asian City (Wuhan, China). Sustainability, 11(19), 5330. https://doi.org/10.3390/su11195330