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دسته بندی:
داده های بزرگ - big data
سال انتشار:
2020
عنوان انگلیسی مقاله:
Determining disaster severity through social media analysis: Testing the methodology with South East Queensland Flood tweets
ترجمه فارسی عنوان مقاله:
تعیین شدت فاجعه از طریق تحلیل رسانه های اجتماعی: آزمایش روش با توییت سیل جنوب شرقی کوئینزلند
منبع:
Sciencedirect - Elsevier - International Journal of Disaster Risk Reduction, 42 (2020) 101360: doi:10:1016/j:ijdrr:2019:101360
نویسنده:
Nayomi Kankanamge a, Tan Yigitcanlar a,*, Ashantha Goonetilleke a, Md. Kamruzzaman b
چکیده انگلیسی:
Social media was underutilised in disaster management practices, as it was not seen as a real-time ground level
information harvesting tool during a disaster. In recent years, with the increasing popularity and use of social
media, people have started to express their views, experiences, images, and video evidences through different
social media platforms. Consequently, harnessing such crowdsourced information has become an opportunity for
authorities to obtain enhanced situation awareness data for efficient disaster management practices. Nonetheless,
the current disaster-related Twitter analytics methods are not versatile enough to define disaster impacts levels as
interpreted by the local communities. This paper contributes to the existing knowledge by applying and
extending a well-established data analysis framework, and identifying highly impacted disaster areas as
perceived by the local communities. For this, the study used real-time Twitter data posted during the 2010–2011
South East Queensland Floods. The findings reveal that: (a) Utilising Twitter is a promising approach to reflect
citizen knowledge; (b) Tweets could be used to identify the fluctuations of disaster severity over time; (c) The
spatial analysis of tweets validates the applicability of geo-located messages to demarcate highly impacted
disaster zones.
Keywords: Social media | Data analytics | Big data | Crowdsourcing | Volunteered geographic information | South East Queensland Floods
قیمت: رایگان
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