Analysis of the use of social networks in acquiring information on disastrous events

Pirnau, Mironela

doi:10.1109/roedunet.2016.7753242

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…Kaur et al [14] reported that because a large amount of data is recorded at the platform, data could be collected from the social media network and analyzed. Moreover, Pirnau [15] studied the effect and disaster of earthquakes by using the real-time information on Twitter to offer information for supporting information for rescue activities. Avvenuti et al [16] suggested that messages posted on the social media from disasters are useful to estimate the condition of the disaster for human beings and buildings.…”

Section: Introductionmentioning

confidence: 99%

Earthquake Shake Detecting by Data Mining from Social Network Platforms

Chuo

2020

Applied Sciences

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This study used social media posts of the related effect of earthquakes to derive seismic shake scale distributions in regions of Taiwan and compared it with the regional seismic scale reported by the Central Weather Bureau (CWB) of Taiwan. This study conducted a context searching to scrawl the relationship phrase on the social media network platform, PTT bulletin board system (BBS), to detect the earthquake shake scale using the keywords of the context. In this investigation a decision tree model for analyzing the semantic words from the context of the target event to detect the earthquake shake scale was devised. The results indicate that we can pick out the keywords to use to detect the earthquake shake scale at about 85%. Furthermore, the results of the derived shake scale show that the four studied cases are in a good agreement with the presented news from the CWB of Taiwan. In this study, the author attempted to develop a quick earthquake shake scale detection model by semantic analysis of the collected earthquake disaster information reported on the social media network platform.

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Section: Introductionmentioning

confidence: 99%