Journalism and semantic web

challenges and proposal of a structured journalism through the 5 Ws

Abstract

Big Data and Natural Language Processing offer new ways of writing, editing, classifying, diffusion and retrieving journalistic texts. However, the academic world has still paid limited attention to it, compared to the contributions of other areas such as linguistics, library sciences and, obviously, computer sciences. However, journalism has much to offer – and to receive – from the semantic web. The present work presents the state of the question beyond the contributions of the field of journalistic communication, looking for common elements between them, to then go on to expose a way of approaching the challenge of structuring journalistic information without it being disruptive or breaking neither with the academic tradition nor with the profession –from discourse theory to style books and writing–. It is proposed to bring the semantic web closer to journalistic practice using the five Ws of journalism as criteria for identifying and classifying content. Using the Ws of journalism –What, Who, Where, When, How and Why– as identification and classification criteria, the content would be organized around its meaning –its semantic function–, taking advantage of the specificities of the narrative structure of the news.