Improving disaster response through Twitter data

Improving disaster response through Twitter data

Twitter data could give disaster relief teams real-time information to provide aid and save lives, thanks to a new algorithm developed by an international team of researchers. A team of researchers from Penn State, the Indian Institute of Technology Kharagpur, and the Qatar Computing Research Institute created an algorithm that analyzes Twitter data to identify smaller disaster-related events, known as sub-events, and generate highly accurate, real-time summaries that can be used to guide response activities. The group presented their paper—"Identifying Sub-events and Summarizing Information from Microblogs during Disasters"—today (July 10) at the 41st International Association for Computing Machinery's Special Interest Group on Information Retrieval Conference on Research and Development in Information Retrieval in Ann Arbor, Michigan. "Several works on disaster-specific summarization in recent times proposed algorithms that mostly provide a general summary of the whole event," the researchers wrote in their paper. Then, volunteers from the United Nations Office for the Coordination of Humanitarian Affairs trained a machine learning system by manually categorizing the tweets into different sub-events, such as food, medicine and infrastructure. Once the system can identify tweets with a high level of accuracy, the researchers allow the system to categorize large amounts of data quickly and accurately without human intervention. "When the topic changes, we observe the machine's accuracy. Then, they created an algorithm to write summaries on the broad event and the identified sub-events. Finally, human evaluators ranked the usefulness and accuracy of sub-events identified by DEPSUB and auto-generated summaries against those created by other existing methods. More information: Identifying Sub-events and Summarizing Information from Microblogs during Disasters.

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Improving disaster response through Twitter data
“We are looking at the crisis as it happens,” said Prasenjit Mitra. “The best source to get timely information during a disaster is social media, particularly microblogs like Twitter. Credit: Thinkstock

Twitter data could give disaster relief teams real-time information to provide aid and save lives, thanks to a new algorithm developed by an international team of researchers.

A team of researchers from Penn State, the Indian Institute of Technology Kharagpur, and the Qatar Computing Research Institute created an algorithm that analyzes Twitter data to identify smaller disaster-related events, known as sub-events, and generate highly accurate, real-time summaries that can be used to guide response activities.

The group presented their paper—”Identifying Sub-events and Summarizing Information from Microblogs during Disasters”—today (July 10) at the 41st International Association for Computing Machinery’s Special Interest Group on Information Retrieval Conference on Research and Development in Information Retrieval in Ann Arbor, Michigan.

“We are looking at the crisis as it happens,” said Prasenjit Mitra, associate dean for research in Penn State’s College of Information Sciences and Technology and a contributor to the study.

“The best source to get timely information during a disaster is social media, particularly microblogs like Twitter,” said Mitra. “Newspapers have yet to print and blogs have yet to publish, so Twitter allows for a near real-time view of an event from those impacted by it.”

Analyzing this data and using it to generate reports related to a sub-topic of a disaster—such as infrastructure damage or shelter needs—could help humanitarian organizations better respond to the varying needs of individuals in an affected area.

Given the volume of data produced, manually managing this process in the immediate aftermath of a crisis is not always…

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