survey

Survey of Text-based Epidemic Intelligence: A Computational Linguistics Perspective

Authors:

Sarvnaz Karimi,

C. Raina MacintyreAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 52, Issue 6

Article No.: 119, Pages 1 - 19

https://doi.org/10.1145/3361141

Published: 16 October 2019 Publication History

Abstract

Epidemic intelligence deals with the detection of outbreaks using formal (such as hospital records) and informal sources (such as user-generated text on the web) of information. In this survey, we discuss approaches for epidemic intelligence that use textual datasets, referring to it as “text-based epidemic intelligence.” We view past work in terms of two broad categories: health mention classification (selecting relevant text from a large volume) and health event detection (predicting epidemic events from a collection of relevant text). The focus of our discussion is the underlying computational linguistic techniques in the two categories. The survey also provides details of the state of the art in annotation techniques, resources, and evaluation strategies for epidemic intelligence.

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Survey of Text-based Epidemic Intelligence: A Computational Linguistics Perspective

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 52, Issue 6

November 2020

806 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3368196

Editor:
Sartaj Sahni
Department of Computer and Information Science and Engineering

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Publication History

Published: 16 October 2019

Accepted: 01 August 2019

Revised: 01 June 2019

Received: 01 August 2018

Published in CSUR Volume 52, Issue 6

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