An AI-Enabled Framework for Real-Time Generation of News Articles Based on Big EO Data for Disaster Reporting

Abstract

In the field of journalism, the collection and processing of information from different heterogeneous sources are difficult and time-consuming processes. In the context of the theory of journalism 3.0, where multimedia data can be extracted from different sources on the web, the possibility of creating a tool for the exploitation of Earth observation (EO) data, especially images by professionals belonging to the field of journalism, is explored. With the production of massive volumes of EO image data, the problem of their exploitation and dissemination to the public, specifically, by professionals in the media industry, arises. In particular, the exploitation of satellite image data from existing tools is difficult for professionals who are not familiar with image processing. In this scope, this article presents a new innovative platform that automates some of the journalistic practices. This platform includes several mechanisms allowing users to early detect and receive information about breaking news in real-time, retrieve EO Sentinel-2 images upon request for a certain event, and automatically generate a personalized article according to the writing style of the author. Through this platform, the journalists or editors can also make any modifications to the generated article before publishing. This platform is an added-value tool not only for journalists and the media industry but also for freelancers and article writers who use information extracted from EO data in their articles.

Theory and Applications of Web 3.0 in the Media Sector

“…The fourth paper focuses on collecting and processing diverse and heterogeneous information, where multimedia data can be extracted from different sources on the Web [19]. In the context of the Journalism 3.0 vision, Tzouma, Zamichos, Efthymiadis, Drosou, and Tzovaras (2021) explore the possibility of creating a tool for utilizing Earth observations, i.e., to manage the massive volumes of image data, thus helping media industry professionals in the selection, usage, and dissemination of such (news) content to the public.…”

“…Fully structured and clarified relations to others (users, events, stories, models, etc.) will expedite data visualization and display purposes, also facilitating interoperability and integration between systems, environments, and applications, interconnecting concepts rather than just documents [4][5][6][7][8][9][10][16][17][18][19]. Thus, journalists and plenary individuals (content contributors and news consumers) will be able to efficiently discover, integrate, and reuse pieces of information from various sources.…”

“…Contemporary Semantic Web and Big Data technologies are continuously elaborated to advance multimodal data analysis concerning information classification, semantic conceptualization and contextualization, content validation, and management automations, which can be primarily deployed in the sensitive news and media domains [1][2][3][4]16,[19][20][21][22][23][24][25][26][27][28][29]. These modular automation and augmentation layers can fuel interaction mechanisms between corporations, machines, and individuals to accelerate crowdsourcing procedures for constructing and maintaining suitable media repositories [16,18,27,29].…”

“…Thereafter, digital literacy initiatives and audience engagement strategies can enhance the impact of SW services in the media world and the broader society. The current Special Issue enlightens the above perspectives through theoretical, algorithmic/technological, and case-study contributions, discussing challenges and state-of-the-art solutions on news detection, classification, (semantic) analysis and evaluation [12,18,27,29,30], automated modeling/prediction, generation, and recommendation of news content [19,[31][32][33], evolution, aesthetics, and integration evaluation of Web 3.0 elements in news websites [34][35][36].…”