| Download | - View final version: Automatic annotation of disposition counts in news articles (PDF, 369 KiB)
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| DOI | Resolve DOI: https://doi.org/10.3233/SHTI250502 |
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| Author | Search for: Rodier, Simon1ORCID identifier: https://orcid.org/0000-0002-6797-629X; Search for: Carter, Dave1ORCID identifier: https://orcid.org/0000-0003-3503-7615 |
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| Affiliation | - National Research Council of Canada. Digital Technologies
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| Format | Text, Article |
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| Conference | EFMI MIE 2025, May 19-21, 2025, Glasgow, Scotland |
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| Subject | case counting; named entity recognition; natural language processing |
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| Abstract | News media aggregate and report disposition counts during crises: how many people are affected, suspected affected, have died, and have recovered or been recovered; and they tend to do so in a timely and trustworthy manner. We present and evaluate a method for identifying these counts in unstructured natural language text, supporting downstream tasks such as automatic creation of epidemic curves. |
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| Publication date | 2025-05-15 |
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| Publisher | IOS Press |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 402e0893-6d85-4fa3-8771-0b0e13360b9f |
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| Record created | 2025-06-04 |
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| Record modified | 2025-06-05 |
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