Academic Journal
Watch and learn : event‑domain term extraction from social networks
| Title: | Watch and learn : event‑domain term extraction from social networks |
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| Authors: | Mamo, Nicholas, Azzopardi, Joel, Layfield, Colin |
| Publisher Information: | SpringerOpen |
| Publication Year: | 2024 |
| Collection: | University of Malta: OAR@UM / L-Università ta' Malta |
| Subject Terms: | Data sets, Social networks, Information retrieval, Computer security, User interfaces (Computer systems), Computer networks -- Security measures |
| Description: | Event tracking algorithms detect and track, but they do not understand what happens in events. Term extraction research has studied the concepts of general domains-computer science, medicine, law-but not What happens in event domains, and not from noisy social networks, where they are popularly narrated. The event structure, the message and its form distinguish event domains from general domains, and formal text from user-generated content. In this article, we present the Event-Aware Term Extractor (EVATE), the first term extractor built for event domains, and the first built for user-generated content. EVATE learns semantically: it tracks events to extract terms that describe What happens, and then ranks them with a termhood statistic designed for event domains. We compared our novel approach with four traditional term extractors in three disparate event domains on data from Twitter (now X). Because EVATE learns semantically, its lexicons described What happens in events better than standard approaches. Even when the term extractors could not adapt to unorthodox event domains, our novel method propped up the others as a semantic re-ranker. The results show that we need algorithms designed for event domains and for user-generated content. Crucially, they also show that we only need one semantic extractor like EVATE to adapt traditional algorithms. ; peer-reviewed |
| Document Type: | article in journal/newspaper |
| Language: | English |
| Relation: | https://www.um.edu.mt/library/oar/handle/123456789/133850 |
| DOI: | 10.1186/s40537-024-01040-2 |
| Availability: | https://www.um.edu.mt/library/oar/handle/123456789/133850 https://doi.org/10.1186/s40537-024-01040-2 |
| Rights: | info:eu-repo/semantics/openAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder |
| Accession Number: | edsbas.1FD23A93 |
| Database: | BASE |
| DOI: | 10.1186/s40537-024-01040-2 |
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