Towards Social Semantic Journalism
| Autor: | Bahareh Rahmanzadeh Heravi, Marie Boran, John Breslin |
|---|---|
| Rok vydání: | 2021 |
| Zdroj: | Proceedings of the International AAAI Conference on Web and Social Media. 6:14-17 |
| ISSN: | 2334-0770 2162-3449 |
| Popis: | User-generated content has become a valuable journalistic tool for news coverage and production. This convergence of new and old media, however, poses several challenges to established news organisations. Social media sites produce a wealth of data in the form of text, images and video that must be processed, compiled and verified within a very short timespan before being incorporated into a news story. This unstructured data that lies scattered across the web can be formalised and organised into a ‘web of data’ by Semantic Web technologies. Specifically, Semantic Web technologies have the potential to formalise and integrate artifacts produced and shared across the Social Web. Social Semantic Journalism proposes the utilisation of Semantic Web technologies, and specifically Social Semantic Web ontologies such as FOAF and SIOC, in the process of news production. This potentially provides a journalistic tool to assist in finding, aggregating and verifying user-generated content for news production. |
| Databáze: | OpenAIRE |
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