SAVITR: A System for Real-time Location Extraction from Microblogs during Emergencies
| Autor: | Avijit Ghosh, Kaustubh Hiware, Ritam Dutt, Rameshwar Bhaskaran |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Social and Information Networks (cs.SI)
FOS: Computer and information sciences Computer science Microblogging Interface (Java) InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL Computer Science - Social and Information Networks 02 engineering and technology computer.software_genre Emergency situations 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Social media Extraction (military) Data mining computer |
| Zdroj: | WWW (Companion Volume) |
| DOI: | 10.48550/arxiv.1801.07757 |
| Popis: | We present SAVITR, a system that leverages the information posted on the Twitter microblogging site to monitor and analyse emergency situations. Given that only a very small percentage of microblogs are geo-tagged, it is essential for such a system to extract locations from the text of the microblogs. We employ natural language processing techniques to infer the locations mentioned in the microblog text, in an unsupervised fashion and display it on a map-based interface. The system is designed for efficient performance, achieving an F-score of 0.79, and is approximately two orders of magnitude faster than other available tools for location extraction. Comment: Presented at SMERP - WWW 2018. Please cite this link for references: https://dl.acm.org/citation.cfm?id=3191623 |
| Databáze: | OpenAIRE |
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