scholarly journals Social Media-Based Identifier for Natural Disaster

2018 ◽  
Vol 288 ◽  
pp. 012039 ◽  
Author(s):  
C Slamet ◽  
A Rahman ◽  
A Sutedi ◽  
W Darmalaksana ◽  
M A Ramdhani ◽  
...  
Keyword(s):  
Social Media ◽  
Natural Disaster

E-Solidarity and Exchange

2019 ◽  
pp. 1266-1276
Author(s):  
David Ramírez Plascencia ◽  
Jorge Ramírez Plascencia
Keyword(s):  
Social Media ◽  
Civil Society ◽  
Natural Disaster ◽  
Public Information ◽  
Tropical Storm ◽  
Final Outcome ◽  
Western Hemisphere ◽  
User Profiles ◽  
Mexican State ◽  
Data Collecting

Between October 24 and 25 in 2015, Mexico faced the strongest hurricane ever registered in the Western Hemisphere, which reached a record of 200 mph (325 km/h) of maximum sustained winds. In spite of pessimist predictions about the final outcome of this natural disaster, at the end, it degraded itself into a tropical storm when landing in the Mexican state of Jalisco. The present research stands in a data collecting process from social media during two moments: a) throughout the happening and b) after the incident. It collected not only information and comments generated in federal and local governmental public profiles but in civil organizations and private user profiles as well. This paper describes how social media helped not only to socialize public information in order to prevent danger but it also served as a link between governmental dependencies and civil society to support affected communities after the event.

scholarly journals Spatio-Temporal Distribution of Negative Emotions in New York City After a Natural Disaster as Seen in Social Media

2018 ◽  
Vol 15 (10) ◽  
pp. 2275 ◽  
Author(s):  
Oliver Gruebner ◽  
Sarah Lowe ◽  
Martin Sykora ◽  
Ketan Shankardass ◽  
SV Subramanian ◽  
...  
Keyword(s):  
New York ◽  
Social Media ◽  
New York City ◽  
Natural Disaster ◽  
York City ◽  
Negative Emotions ◽  
Temporal Distribution ◽  
Census Tracts ◽  
Post Disaster ◽  
Over Time

Disasters have substantial consequences for population mental health. We used Twitter to (1) extract negative emotions indicating discomfort in New York City (NYC) before, during, and after Superstorm Sandy in 2012. We further aimed to (2) identify whether pre- or peri-disaster discomfort were associated with peri- or post-disaster discomfort, respectively, and to (3) assess geographic variation in discomfort across NYC census tracts over time. Our sample consisted of 1,018,140 geo-located tweets that were analyzed with an advanced sentiment analysis called ”Extracting the Meaning Of Terse Information in a Visualization of Emotion” (EMOTIVE). We calculated discomfort rates for 2137 NYC census tracts, applied spatial regimes regression to find associations of discomfort, and used Moran’s I for spatial cluster detection across NYC boroughs over time. We found increased discomfort, that is, bundled negative emotions after the storm as compared to during the storm. Furthermore, pre- and peri-disaster discomfort was positively associated with post-disaster discomfort; however, this association was different across boroughs, with significant associations only in Manhattan, the Bronx, and Queens. In addition, rates were most prominently spatially clustered in Staten Island lasting pre- to post-disaster. This is the first study that determined significant associations of negative emotional responses found in social media posts over space and time in the context of a natural disaster, which may guide us in identifying those areas and populations mostly in need for care.

The Role of Social Media During a Natural Disaster: A Case Study of the 2011 Thai Flood

2014 ◽  
Vol 11 (03) ◽  
pp. 1440012 ◽  
Author(s):  
Alisa Kongthon ◽  
Choochart Haruechaiyasak ◽  
Jaruwat Pailai ◽  
Sarawoot Kongyoung
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Natural Disaster ◽  
Thai People ◽  
Twitter Users ◽  
Use Of Social Media ◽  
Share Information ◽  
Multiple Analysis

Recently, social media has become a key platform that allowed people to interact and share information. The use of social media is expanding significantly and can serve a variety of purposes. Over the last few years, users of social media have played an increasing role in the dissemination of emergency and disaster information. In this paper, we conduct a case study exploring how Thai people used social media such as Twitter in response to one of the country's worst disasters in recent history: the 2011 Thai Flood. We combine multiple analysis methods in this study, including content analysis of Twitter messages, trend analysis of different message categories, and influential Twitter users analysis. This study helps us understand the role of social media in time of natural disaster.

scholarly journals Disease and Social Media in Post-Natural Disaster Recovery Philippines

2021 ◽  
Author(s):  
Lauren E. Charles ◽  
Courtney D. Corley
Keyword(s):  
Social Media ◽  
Natural Disasters ◽  
Natural Disaster ◽  
Disease Surveillance ◽  
Disaster Recovery ◽  
Recovery Period ◽  
Disease Outbreaks ◽  
The Philippines ◽  
Surveillance Program ◽  
Multilinear Regression

AbstractIntroductionThe Philippines is plagued with natural disasters and resulting precipitating factors for disease outbreaks. The developing country has a strong disease surveillance program during and post-disaster phases; however, latent disease contracted during these emergency situations emerges once the Filipinos return to their homes. Coined the social media capital of the world, the Philippines provides an opportunity to evaluate the potential of social media use in disease surveillance during the post-recovery period. By developing and defining a non-traditional method for enhancing detection of infectious diseases post-natural disaster recovery in the Philippines, this research aims to increase the resilience of affected developing countries through advanced passive disease surveillance with minimal cost and high impact.MethodsWe collected 50 million geo-tagged tweets, weekly case counts for six diseases, and all natural disasters from the Philippines between 2012 and 2013. We compared the predictive capability of various disease lexicon-based time series models (e.g., Twitter’s BreakoutDetection, Autoregressive Integrated Moving Average with Explanatory Variable [ARIMAX], Multilinear regression, and Logistic regression) and document embeddings (Gensim’s Doc2Vec).ResultsThe analyses show that the use of only tweets to predict disease outbreaks in the Philippines has varying results depending on which technique is applied, the disease type, and location. Overall, the most consistent predictive results were from the ARIMAX model which showed the significance in tweet value for prediction and a role of disaster in specific instances.DiscussionOverall, the use of disease/sick lexicon-filtered tweets as a predictor of disease in the Philippines appears promising. Due to the consistent and large increase use of Twitter within the country, it would be informative to repeat analysis on more recent years to confirm the top method for prediction. In addition, we suggest that a combination disease-specific model would produce the best results. The model would be one where the case counts of a disease are updated periodically along with the continuous monitoring of lexicon-based tweets plus or minus the time from disaster.

scholarly journals Who Has to Tell Their Trauma Story and How Hard Will It Be? Influence of Cultural Stigma and Narrative Redemption on the Storying of Sexual Violence

2019 ◽  
Author(s):  
Brianna C Delker ◽  
Rowan Salton ◽  
Kate C. McLean ◽  
Moin Syed
Keyword(s):  
Mental Health ◽  
United States ◽  
Social Media ◽  
Sexual Violence ◽  
Natural Disaster ◽  
The United States ◽  
Societal Implications ◽  
The Public ◽  
Cultural Preference ◽  
Cultural Stigma

Although survivors of sexual violence have shared their stories with the public on social media and mass media platforms in growing numbers, less is known about how general audiences perceive such trauma stories. These perceptions can have profound consequences for survivor mental health. In the present experimental, vignette-based studies, we anticipated that cultural stigma surrounding sexual violence and cultural preference for positive (redemptive) endings to adversity in the United States (U.S.) would shape perceptions. Four samples of U.S. adults (N=1872) rated first-person narratives of 6 more stigmatizing (i.e., sexual violence) or less stigmatizing (e.g., natural disaster) traumatic events. Confirming pre-registered hypotheses, sexual violence trauma (versus other types of trauma) stories were perceived as more difficult to tell, and their storytellers less likeable, even when they had redemptive endings. Disconfirming other pre-registered hypotheses, redemptive (versus negative) story endings did not boost the perceived likelihood or obligation to share a sexual violence trauma story. Rather, redemptive (versus negative) story endings only boosted the perceived likelihood, obligation, and ease of telling other, less stigmatizing types of trauma stories. Findings suggest that sexual violence survivors do not benefit, to the same degree as other survivors, from telling their stories with the culturally valued narrative template of redemption. Clinical and societal implications of the less receptive climate for sexual violence stories are discussed.

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