Identifying Seekers and Suppliers in Social Media Communities to Support Crisis Coordination
Effective crisis management has long relied on both the formal and informal response communities. Social media platforms such as Twitter increase the participation of the informal response community in crisis response. Yet, challenges remain in realizing the formal and informal response communities as a cooperative work system. We demonstrate a supportive technology that recognizes the existing capabilities of the informal response community to identify needs (seeker behavior) and provide resources (supplier behavior), using their own terminology. To facilitate awareness and the articulation of work in the formal response community, we present a technology that can bridge the differences in terminology and understanding of the task between the formal and informal response communities. This technology includes our previous work using domain-independent features of conversation to identify indications of coordination within the informal response community. In addition, it includes a domain-dependent analysis of message content (drawing from the ontology of the formal response community and patterns of language usage concerning the transfer of property) to annotate social media messages. The resulting repository of annotated messages is accessible through our social media analysis tool, Twitris. It allows recipients in the formal response community to sort on resource needs and availability along various dimensions including geography and time. Thus, computation indexes the original social media content and enables complex querying to identify contents, players, and locations. Evaluation of the computed annotations for seeker-supplier behavior with human judgment shows fair to moderate agreement. In addition to the potential benefits to the formal emergency response community regarding awareness of the observations and activities of the informal response community, the analysis serves as a point of reference for evaluating more computationally intensive efforts and characterizing the patterns of language behavior during a crisis.
Key wordscoordination crisis informatics cooperative crisis response crisis response coordination organizational sensemaking psycholinguistics spatio-temporal analysis twitris seeker-supplier behavior semantic web
This work is supported by the NSF (IIS-1111182, 09/01/2011 - 08/31/2014) SoCS program. We thank the NSF for their generous support, our colleagues for the valuable comments on the draft and preliminary discussion about designing a coordination analysis framework, James Gruenberg from Wright State’s Calamityville for valuable insight into disaster management, and research assistants, especially Dylan Clericus (undergraduate), Meagan Newman, and Harry Abramovitz.
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