Emergency-relief coordination on social media: Automatically matching resource requests and offers
Emergency-relief coordination on social media: Automatically matching resource requests and offers
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社交媒体上的紧急救援协调：自动匹配资源请求和供应
作者：
Hemant Purohit;Carlos Castillo;Fernando Diaz;A. Sheth;P. Meier
受灾害影响的社区越来越多地转向社交媒体进行沟通和协调。这包括关于紧急情况期间所需资源的需要（需求）和提供（供应）的报告。查明这些请求并将其与可能的响应者相匹配，可以大大加快紧急救济工作。目前灾害管理机构的工作是劳动密集型的，人们对自动化工具有很大的兴趣。我们提出了机器学习方法来自动识别和匹配通过社交媒体传达的物品和服务的需求和提供，如住所，钱，衣服等。例如，一条消息，如“我们正在协调为受飓风桑迪影响的家庭提供衣服/食品。如果你想捐赠，DM我们”可以与这样的消息相匹配：“我有一堆衣服，我想捐赠给飓风桑迪的受害者。有谁知道我在哪里/怎么做？”与传统搜索相比，我们的结果可以显着提高灾害响应机构的匹配工作。
Disaster affected communities are increasingly turning to social media for communication and coordination. This includes reports on needs (demands) and offers (supplies) of resources required during emergency situations. Identifying and matching such requests with potential responders can substantially accelerate emergency relief efforts. Current work of disaster management agencies is labor intensive, and there is substantial interest in automated tools.We present machine–learning methods to automatically identify and match needs and offers communicated via social media for items and services such as shelter, money, clothing, etc. For instance, a message such as “we are coordinating a clothing/food drive for families affected by Hurricane Sandy. If you would like to donate, DM us” can be matched with a message such as “I got a bunch of clothes I’d like to donate to hurricane sandy victims. Anyone know where/how I can do that?” Compared to traditional search, our results can significantly improve the matchmaking efforts of disaster response agencies.