A Method for Extracting Task-related Information from Social Media based on Structured Domain Knowledge
In a recent conference paper, an innovative method was developed for extracting task-related information from social media based on structured domain knowledge. This publication is the most recent result of the productive collaboration between the AGORA Group and the Chair of Information Systems and Supply Chain Management (ERCIS) of University of Münster, Germany. The full paper can be found here and its abstract is presented below:
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.
On August 15th, Daniel Link, AGORA’s partner from University of Münster, presented the paper in Puerto Rico at the 2015 Americas Conference on Information Systems (AMCIS). This paper is another important outcome from this collaboration between AGORA Group and University of Münster. Besides this, another paper and a research stay had already been done.