Social Media Text Mining for Decision Support in Natural Disaster Management in Sri Lanka
With the popularity of the internet and
smart devices, social media is viral today among individuals in
almost all the ages which help them to create and share their
personal feelings, experiences, ideas, as well as information
with others connected to them over a computer, mediated
technology. Due to this nature when there are emergencies and
natural disasters these social media applications tend to be
flooded with content generated from the public who affected,
who are looking for their family members and friends, who are
looking for information as well as with the people engage in
humanitarian activities.Therefore, social media has become the
first to generate related information when there is a
catastrophic event before any of news sites or government
bodies engage in disaster management. This social media
content is quick accurate and subjective during disaster
situations, therefore,can be used as an asset to reduce risk and
build awareness among the public about the disaster as well as
to provide decision making support to relief efforts. This
research focuses on building decision making support using
social media content generated during disaster situations in the
Sri Lankan context. Mainly the content will be tweets posted by
the public during a natural disaster and consisting of text
written in English. Therefore,situational awareness building
will be done using text mining techniques in this study since the
content is unstructured.
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