Shibuya, Y. (2017) Mining Social Media for Disaster Management: Leveraging Social Media Data for Community Recovery. 2017 IEEE International Conference on Big Data (Big Data), Boston, 11-14 December 2017, 3111-3118.
https://doi.org/10.1109/BigData.2017.8258286

has been cited by the following article:

• TITLE: Application of Social Media Tool in Disaster Management in Disaster-Prone Communities in Freetown, Sierra Leone

  AUTHORS: Ibrahim Abdulai Sawaneh, Luo Fan, Brima Sesay

  KEYWORDS: Social Media Use, Disaster Management, Disaster-Prone Community, Task Complexity, Ability, Effort

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.13 No.6, June 25, 2023

  ABSTRACT: This study used both the “digital divide” and “attribution theory” to analyze the propensity of social media use by disaster-prone communities. The study focused on the variables that may affect how social media is used for disaster management. Structural equation modeling (SEM) was utilized in the study to analyze the data and test the hypotheses after using a survey questionnaire to collect the data. The study’s findings show that: 1) communities that are vulnerable to disasters are less likely to use social media for disaster management, 2) personal effort and intention to use social media for disaster management are positively correlated, and 3) task complexity and intention to use social media for disaster management are negatively correlated. The study added to the body of knowledge regarding the role social media plays in disaster management.