Saving Lives and Changing Minds with Twitter in Disasters and Pandemics: A Literature Review
Abstract
:1. Introduction
- What are Twitter’s functions in a disaster?
- How can governments and emergency organizations use Twitter to manage disasters more effectively?
- How was Twitter used at different stages of disaster management including mitigation, preparedness, response and recovery?
2. Materials and Methods
2.1. Eligibility
2.2. Search Strategy
2.3. Selection Processes
2.4. Data Extraction
2.5. Data Synthesis
2.6. Search Strategy
3. Results
3.1. Early Warning
3.2. Disseminating Information
3.3. Advocacy
3.4. Personal Gains
3.5. Assessment
3.6. Risk Communication
3.7. Tracking Public Mood
3.8. Geographical Analysis
3.9. Charity
3.10. Collaboration with Influencers
3.11. Building Trust
3.12. Other Issues
4. Discussion
5. Conclusions
5.1. Implications for Practice
5.2. Implications for Policy
5.3. Implications for Research
Author Contributions
Funding
Conflicts of Interest
References
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No. | Disaster | Finding | Disaster Phase | Country | Ref. |
---|---|---|---|---|---|
1 | Typhoon | People and organizations have used Twitter more often to retweet second-hand information/social networking users in Philippines are more likely to pay attention to news released in traditional media than social media. | response | Philippines | (Takahashi et al. 2015) |
2 | Earthquake, Tsunami | The results suggest that Twitter can be used to track and measure the public’s mood after disasters. | Response, Recovery | Japan | (Doan et al. 2011) |
3 | Wildfire | The geographic awareness of people is strong about critical events and people are interested in tweeting about fire damage, firefighting and thanking firefighters/official tweets play a key role in the firefighting network. | Preparedness, Response | USA | (Wang et al. 2016) |
4 | Earthquake | Rumors about earthquakes spread more than anything else on Twitter. | Response | Chile | (Mendoza et al. 2010) |
5 | Earthquake | Twitter was used as a tool to report on the situation by the affected people. This article suggests that Twitter can be used as a tool for rapid assessment of an accident, as well as for the publication of accurate information by officials. | Response | Japan | (Acar and Muraki 2011) |
6 | Earthquake | Twitter is useful as a tool to show people’s mental health, especially in the early days of a disaster. | Response | Japan | (Cho et al. 2013) |
7 | Earthquake | During an earthquake, organizations used Twitter as a tool for risk communication, to collect public donations and to provide psychological support. | Response, Recovery | Haiti | (Gurman and Ellenberger 2015) |
8 | Earthquake | Twitter was used for disaster assessment, response monitoring and to help the affected people. | Response | Haiti | (Smith 2010) |
9 | Storm | A lot of first-hand information was published about the current situation. Twitter is useful for disaster assessment. | Response | USA | (Mukkamala and Beck 2016) |
10 | Tornado | People trusted personal accounts more than governmental accounts to find out about a tornado. Influential people play a big role in providing the right information. Using the right hashtag will help to spread information on Twitter. | Response | USA | (Cooper et al. 2015) |
11 | Earthquake | Twitter acted as an effective and efficient tool for communication between people and aid organizations in an earthquake. | Response | Nepal | (Subba and Bui 2017) |
12 | Storm | Establishing a strategy for using Twitter in times of disaster is essential. Twitter is a great tool for publishing content, but it has been suggested that influential people should be used to publish it. | Preparedness, Response | USA | (Chatfield and Reddick 2017) |
13 | Tsunami | Twitter is a powerful tool for early warning during tsunamis, especially for Indonesia which has a high population distribution. | Preparedness | Indonesia | (Carley et al. 2016) |
14 | Volcanic eruption | At the time of the eruption, a lot of misinformation was spread. Therefore, it is necessary for government agencies to have an information strategy in case of disasters so that they can publish the correct information from the first moment. | Response | Iceland | (Sreenivasan et al. 2011) |
15 | Earthquake, Tsunami | A third of the tweets were released from low credibility sources. Tweets published by anonymous and unidentified accounts have lowered credibility. | Response | Japan | (Thomson et al. 2012) |
16 | Flood | Tweet analysis helped to identify the effects of flooding on people’s mental health. This can affect the design of psychosocial support programs. | Response, Recovery | India | (Karmegam and Mappillairaju 2020) |
17 | Ebola Outbreak | To spread information about Ebola, influential people on Twitter shared information. It is recommended that these people be helped to publish correct information. | Preparedness | Global | (Liang et al. 2019) |
18 | COVID-19 pandemic | Publishing false information about pandemics has reached alarming levels that endanger public health. | Preparedness | Global | (Kouzy et al. 2020) |
19 | COVID-19 pandemic | There was a geographic relationship between the flow of information about the pandemic and the identification of new cases of COVID-19. | Preparedness, Response | Global | (Singh et al. 2020) |
20 | COVID-19 pandemic | Using Twitter text and image analysis, the prevalence in each geographical area can be predicted. | Preparedness | Global | (Jahanbin and Rahmanian 2020) |
21 | COVID-19 pandemic | Twitter bots are used to promote misinformation and political information about COVID-19. | Preparedness | USA | (Ferrara 2020) |
22 | COVID-19 pandemic | At the same time, Twitter played a useful role in promoting positive information and a negative role in disseminating misinformation about the COVID-19. | Preparedness | Global | (Rosenberg et al. 2020) |
23 | COVID-19 pandemic | The community’s sentiment can be assessed using tweet analysis. | Response | USA | (Medford et al. 2020) |
24 | COVID-19 pandemic | Policies adopted in the United States and their effects on society were analyzed using Twitter. | Response | USA | (Sharma et al. 2020) |
25 | COVID-19 pandemic | Analyzing the tweets of the leaders of the G7 on the coronavirus showed that Twitter has become a powerful tool for world leaders to disseminate information about public health during the pandemic. | Preparedness | G7 countries | (Rufai and Bunce 2020) |
26 | COVID-19 pandemic | Tweet analysis during the COVID-19 pandemic in the United States showed that this pandemic has a political effect on society. Twitter bots played a major role in disseminating invalid information. | Preparedness | USA | (Yang et al. 2020) |
27 | COVID-19 pandemic | The dominant discourse in society on the COVID-19 pandemic can be identified and analyzed on Twitter. | Response | Global | (Wicke and Bolognesi 2020) |
28 | COVID-19 pandemic | Wrong information was widely published on Twitter. | preparedness | Global | (Sharma et al. 2020) |
29 | COVID-19 pandemic | Analyzing Twitter data on the specifications of people with coronavirus, it was suggested that in addition to using clinical data about people with the virus, Twitter data should also be used. | Response | Global | (Sarker et al. 2020) |
30 | COVID-19 pandemic | Using tweet analysis in the United States, various aspects of social distancing (methods of preventing infection) were identified and analyzed. | Preparedness | USA | (Kwon et al. 2020) |
31 | COVID-19 pandemic | The study found that tweet analysis could be crucial in the geographical distribution and density of the virus outbreak in the UK. | Response | UK | (Golder et al. 2020) |
32 | COVID-19 pandemic | The study found that tweet analysis could help to identify geographic distribution and the prevalence of the virus in the United States. | Response | USA | (Gharavi et al. 2020) |
33 | COVID-19 pandemic | Tweet analysis showed that a large number of tweets have stigmatized China because the first cases of this pandemic were observed in China. | Response | USA | (Budhwani and Sun 2020) |
34 | Outbreaks | Twitter is useful in predicting disease outbreaks. | Mitigation | Global | (St Louis and Zorlu 2012) |
35 | Zika outbreak | Tweets showed the social impacts of the epidemic, the role of organizations and policies, information on the transmission of the disease and the lessons learned. | Preparedness, Response | Global | (Fu et al. 2016) |
36 | Flu outbreak | The use of Twitter data is more accurate in modeling flu epidemic prediction than Google data. | Response | USA | (Paul et al. 2014) |
37 | Yellow Fever outbreak | The amount of misinformation about yellow fever was much larger than that of correct information, and misinformation was shared and retweeted, which can be dangerous to public health. | Preparedness | Global | (Ortiz-Martínez and Jiménez-Arcia 2017) |
38 | Outbreaks | Twitter can act as an early warning system during epidemics. Twitter can also help to detect the prevalence of geography at different times and places and can be analyzed from time to time. | Preparedness | Global | (Kanhabua and Nejdl 2013) |
39 | Flu and Ebola Outbreaks | Analyzing tweets about the 2009 and 2014 Ebola epidemics revealed that Twitter could help to analyze the state of mental health and general fear during the epidemic. | Response | Global | (Ahmed et al. 2018) |
40 | Ebola outbreak | During the 2014 Ebola outbreak in East Africa, a lot of misinformation was spread on Twitter. Proper information needs to be disseminated through influential people during epidemics. | Preparedness | East Africa | (Oyeyemi et al. 2014) |
41 | Flu outbreak | Twitter was used as a tool for early warning during the 2009 flu and risk communications in the United States. | Preparedness | USA | (Kostkova et al. 2014) |
42 | Ebola outbreak | Twitter helped to spread information about Ebola in Nigeria. | Preparedness | Nigeria | (Carter 2014) |
43 | Outbreaks | The potential value of incorporating Twitter into existing unplanned school closure (USC) monitoring systems was examined. | Response | USA | (Ahweyevu et al. 2020) |
44 | Influenza Epidemics | Extending the capacity of surveillance systems for detecting emerging influenza was examined. | Response | Korea | (Woo et al. 2017) |
45 | Ebola | Social media can be used to communicate possible disease outbreaks in a timely manner, and using online search data to tailor messages to align with the public health interests of their constituents was considered by government officials. | Preparedness | USA | (Wong and Harris 2017) |
Stakeholders | Type of Hazards | Twitter Functions | Tweets Characteristics | Disaster Risk Management |
---|---|---|---|---|
Governments, Emergency organizations, Celebrities, People, News agencies, Donors, Affected people | Disasters triggered by natural and technological hazards, pandemics and complex disasters | Early warning, disseminating information, advocacy, assessment, risk communication, public sentiment, geographical analysis, charity, collaboration with influencers and building trust | Transparency, on-time messages, using different local languages, Using different media (text, video, photo) | Using Twitter during different phases including mitigation, preparedness, response and recovery |
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Seddighi, H.; Salmani, I.; Seddighi, S. Saving Lives and Changing Minds with Twitter in Disasters and Pandemics: A Literature Review. Journal. Media 2020, 1, 59-77. https://doi.org/10.3390/journalmedia1010005
Seddighi H, Salmani I, Seddighi S. Saving Lives and Changing Minds with Twitter in Disasters and Pandemics: A Literature Review. Journalism and Media. 2020; 1(1):59-77. https://doi.org/10.3390/journalmedia1010005
Chicago/Turabian StyleSeddighi, Hamed, Ibrahim Salmani, and Saeideh Seddighi. 2020. "Saving Lives and Changing Minds with Twitter in Disasters and Pandemics: A Literature Review" Journalism and Media 1, no. 1: 59-77. https://doi.org/10.3390/journalmedia1010005