Collaboration among humanitarian relief organizations and volunteer technical communities : identifying research opportunities and challenges through a systematic literature review

Collaboration is the foundation to strengthen disaster preparedness and for effective emergency response actions at all levels. Some studies have highlighted that remote volunteers, i.e., volunteers supported by Web 2.0 technologies, possess the potential to strengthen humanitarian relief organizations by offering information regarding disaster-affected people and infrastructure. Although studies have explored various aspects of this topic, none of those provided an overview of the state-of-the-art of researches on the collaboration among humanitarian organizations and communities of remote volunteers. With the aim of overcoming this gap, a systematic literature review was conducted on the existing research works. Therefore, the main contribution of this work lies in examining the state of research in this field and in identifying potential research gaps. The results show that most of the research works addresses the general domain of disaster management, whereas only few of them address the domain of humanitarian logistics. Collaboration among Humanitarian Relief Organizations and Volunteer Technical Communities: Identifying Research Opportunities and Challenges through a Systematic Literature Review (PDF Download Available). Available from: https://www.researchgate.net/publication/315790817_Collaboration_among_Humanitarian_Relief_Organizations_and_Volunteer_Technical_Communities_Identifying_Research_Opportunities_and_Challenges_through_a_Systematic_Literature_Review [accessed May 26, 2017]

The Effect of Mobile Gamification on Brand Loyalty

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A Method for Extracting Task-related Information from Social Media based on Structured Domain Knowledge

Social media platforms have come into the focus of research as sources of information about the unfolding situation in disaster contexts. Incorporating information from social media into decision-making is still difficult though. One reason may be that the prevalent approach to data analysis works bottom-up, which has several limitations. In this paper, we adopt a top-down approach by means of a novel keyword-based method for identifying potentially relevant information in social media data based on structured knowledge of activities undertaken in a domain. The application of the method to the context of humanitarian logistics using four social media datasets shows its capability to identify potentially relevant information via reference tasks and to match identified information with decision-makers’ activities. In addition, we offer a first set of domain-specific keywords to identify information related to infrastructure and resources in humanitarian logistics

Extracting Task-related Information Using Structured Domain Knowledge A Method for Extracting Task-related Information from Social Media based on Structured Domain Knowledge

Abstract Social media platforms have come into the focus of research as sources of information about the unfolding situation in disaster contexts. Incorporating information from social media into decision-making is still difficult though. One reason may be that the prevalent approach to data analysis works bottom-up, which has several limitations. In this paper, we adopt a top-down approach by means of a novel keyword-based method for identifying potentially relevant information in social media data based on structured knowledge of activities undertaken in a domain. The application of the method to the context of humanitarian logistics using four social media datasets shows its capability to identify potentially relevant information via reference tasks and to match identified information with decision-makers' activities. In addition, we offer a first set of domain-specific keywords to identify information related to infrastructure and resources in humanitarian logistics