Coordinating human and machine intelligence to classify microblog communications in crises

Muhammad Imran, Carlos Castillo, Ji Lucas, Patrick Meier, Jakob Rogstadius

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

69 Citations (Scopus)

Abstract

An emerging paradigm for the processing of data streams involves human and machine computation working together, allowing human intelligence to process large-scale data. We apply this approach to the classification of crisis-related messages in microblog streams. We begin by describing the platform AIDR (Artificial Intelligence for Disaster Response), which collects human annotations over time to create and maintain automatic supervised classifiers for social media messages. Next, we study two significant challenges in its design: (1) identifying which elements must be labeled by humans, and (2) determining when to ask for such annotations to be done. The first challenge is selecting the items to be labeled by crowd sourcing workers to maximize the productivity of their work. The second challenge is to schedule the work in order to reliably maintain high classification accuracy over time. We provide and validate answers to these challenges by extensive experimentation on real world datasets.

Original languageEnglish
Title of host publicationISCRAM 2014 Conference Proceedings - 11th International Conference on Information Systems for Crisis Response and Management
PublisherThe Pennsylvania State University
Pages712-721
Number of pages10
ISBN (Print)9780692211946
Publication statusPublished - 2014
Event11th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2014 - University Park, PA, United States
Duration: 1 May 20141 May 2014

Publication series

NameISCRAM 2014 Conference Proceedings - 11th International Conference on Information Systems for Crisis Response and Management

Conference

Conference11th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2014
Country/TerritoryUnited States
CityUniversity Park, PA
Period1/05/141/05/14

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